Data Scientist, Finance

<p>Hims & Hers is the leading health and wellness platform, on a mission to help the world feel great through the power of better health. We are redefining healthcare by putting the customer first and delivering access to care that is affordable, accessible, and personal, from diagnosis to treatment to delivery. No two people are the same, so we provide access to personalized care designed for results. By normalizing health & wellness challenges and innovating on their solutions, we’re making better health outcomes easier to achieve. </p><p>Hims & Hers is a public company, traded on the NYSE under the ticker symbol “HIMS.” To learn more about the brand and offerings, you can visit <a href='http://hims.com/about'>hims.com/about</a> and <a href='http://hims.com/how-it-works'><u>hims.com/how-it-works</u></a> . For information on the company’s outstanding benefits, culture, and its talent-first flexible/remote work approach, see below and visit <a href='http://www.hims.com/careers-professionals'><u>www.hims.com/careers-professionals</u></a>.</p><h2>About the Role:</h2><p>As a Staff Data Scientist at Hims & Hers, you are a technical leader and a 'force multiplier' for our data organization. You do not just solve the most difficult problems; you identify which problems are worth solving to move the needle for our customers. You will serve as a technical anchor, simplifying ambiguous problems into executable paths for the team.</p><p>In this role, you will bridge the gap between business strategy and production-ready machine learning. Whether you are building frameworks for growth, optimizing our supply chain, or refining marketing attribution, you will ensure our data products are technically sound, scalable, and built to deliver measurable business results.</p><h2>You Will:</h2><ul><li><p><strong>Architect the 0-to-1 Foundation:</strong> Lead the design and implementation of automated ML systems. You know how to balance 'doing it right' with 'doing it fast,' making pragmatic architectural choices (build vs. buy, simple vs. complex) while rolling up your sleeves to write production code and establish our core ML infrastructure.</p></li><li><p><strong>Translate Business Needs:</strong> Turn ambiguous business questions (from customer acquisition to churn dynamics) into concrete technical roadmaps that deliver clear, actionable results</p></li><li><p><strong>Drive Execution and Reliability:</strong> Lead the end-to-end deployment of ML products, ensuring they are not just accurate but robust, maintainable, and fully integrated into our production infrastructure</p></li><li><p><strong>Connect Technical & Business Goals:</strong> Partner across Engineering, Product, and Business to ensure our technical strategy is solving the right business problems and moving our core metrics</p></li><li><p><strong>Define Technical Standards:</strong> Act as a force multiplier by establishing the standards for model development. You will lead design docs and peer reviews that ensure our work is reproducible and integrates with the work of our Data and Analytics Engineering partners</p></li><li><p><strong>Own the Results:</strong> Take accountability for the full model lifecycle, from the initial data design through to the long-term performance and business value of production systems</p></li><li><p><strong>Mentorship & Coaching:</strong> Actively mentor Senior and Mid-level Data Scientists, elevating the technical bar and fostering a culture of continuous learning across the data organization.</p></li></ul><h2>Experience & Skills:</h2><ul><li><p><strong>8+ years of experience</strong> in Data Science or ML Engineering, with a proven track record of building production systems that deliver measurable business impact</p></li><li><p><strong>Technical Mastery:</strong> High proficiency in Python and SQL. Expert-level experience with the Python data stack (pandas, NumPy, scikit-learn) and at least one major ML framework (such as PyTorch or XGBoost/LightGBM)</p></li><li><p><strong>Systemic Problem Solving:</strong> Ability to work on unique issues requiring conceptual thinking and broad impact. You know how to build for long-term scalability while delivering immediate value</p></li><li><p><strong>Leadership & Influence:</strong> Proven ability to influence without authority. You can translate complex technical logic into compelling narratives for executive leadership</p></li><li><p><strong>Engineering Rigor:</strong> Experience with CI/CD, ML Ops, and managing the full lifecycle of models in a cloud-based production environment (AWS or GCP)</p></li><li><p><strong>Education:</strong> BS, MS, or PhD in a quantitative field (Data Science, Statistics, Economics, CS, Applied Math, etc.) or equivalent field expertise</p></li></ul><h2> </h2><h2>Preferred Qualifications:</h2><ul><li><p><strong>0-to-1 Execution:</strong> Experience taking the very first machine learning models in an organization from exploratory notebooks to reliable, automated production pipelines.</p></li><li><p><strong>Advanced Business ML (Experience in 1-2 of the following):</strong></p><ul><li><p><strong>Customer Behavior & Propensity Modeling:</strong> Building predictive models for churn, propensity-to-buy, lead scoring, or lifetime value (LTV) to directly drive targeted marketing and product interventions.</p></li><li><p><strong>Applied Forecasting:</strong> Time-series forecasting, anomaly detection, or handling non-stationary data for demand or revenue planning.</p></li><li><p><strong>Optimization:</strong> Building engines for marketing spend, inventory management, or resource allocation.</p></li><li><p><strong>Causal Inference:</strong> Designing robust experiments (e.g., quasi-experiments, difference-in-differences) to measure true business impact beyond standard A/B testing.</p></li></ul></li></ul><h2>Our Benefits (there are more but here are some highlights):</h2><ul><li><p>Competitive salary & equity compensation for full-time roles</p></li><li><p>Unlimited PTO, company holidays, and quarterly mental health days</p></li><li><p>Comprehensive health benefits including medical, dental & vision, and parental leave</p></li><li><p>Employee Stock Purchase Program (ESPP)</p></li><li><p>401k benefits with employer matching contribution</p></li><li><p>Offsite team retreats</p></li></ul><p>We are committed to building a workforce that reflects diverse perspectives and prioritizes ethics, wellness, and a strong sense of belonging. If you're excited about this role, we encourage you to apply—even if you're not sure if your background or experience is a perfect match.</p><p>Hims considers all qualified applicants for employment, including applicants with arrest or conviction records, in accordance with the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance, the California Fair Chance Act, and any similar state or local fair chance laws.</p><p>It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.</p><p>Hims & Hers is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, please contact us at <a href='mailto:[email protected]'><u>[email protected]</u></a> and describe the needed accommodation. Your privacy is important to us, and any information you share will only be used for the legitimate purpose of considering your request for accommodation. Hims & Hers gives consideration to all qualified applicants without regard to any protected status, including disability. Please do not send resumes to this email address.</p><p>To learn more about how we collect, use, retain, and disclose Personal Information, please visit our <a href='https://www.hims.com/global-candidate-privacy-statement'><u>Global Candidate Privacy Statement</u></a>.</p>

AL, AK, AZ, AR, CA, CO, CT, DE, FL, GA, HI, ID, IL, IN, IA, KS, KY, LA, ME, MD, MA, MI, MN, MS, MO, MT, NE, NV, NH, NJ, NM, NY, NC, ND, OH, OK, OR, PA, RI, SC, SD, TN, TX, UT, VT, VA, WA, DC, WV, WI, WY

Data

<p>Hims & Hers is the leading health and wellness platform, on a mission to help the world feel great through the power of better health. We are redefining healthcare by putting the customer first and delivering access to care that is affordable, accessible, and personal, from diagnosis to treatment to delivery. No two people are the same, so we provide access to personalized care designed for results. By normalizing health & wellness challenges and innovating on their solutions, we’re making better health outcomes easier to achieve. </p><p>Hims & Hers is a public company, traded on the NYSE under the ticker symbol “HIMS.” To learn more about the brand and offerings, you can visit <a href='http://hims.com/about'>hims.com/about</a> and <a href='http://hims.com/how-it-works'><u>hims.com/how-it-works</u></a> . For information on the company’s outstanding benefits, culture, and its talent-first flexible/remote work approach, see below and visit <a href='http://www.hims.com/careers-professionals'><u>www.hims.com/careers-professionals</u></a>.</p><h2>About the Role:</h2><p>We're hiring a Principal Data Engineer to set the technical direction for data at Hims & Hers. This is the most senior individual contributor role in Data Platform Engineering (DPE), and the scope is deliberately larger than DPE: the architecture you define determines how Software Engineering, Analytics Engineering, and Data Science build on data for millions of patients across our Telehealth, prescription, and wellness products.</p><p>The platform runs on GCP BigQuery, Airflow on Astronomer/EKS, dbt, Confluent Kafka, Databricks Delta Lake, and Terraform/OpenTofu. Two foundational pieces are being built from scratch right now: a streaming platform and a lower environments strategy. The most consequential open question is whether streaming stays scoped to analytics or extends into production and model evaluation paths that other teams depend on. That call is yours to make, and the company will live with it for years.</p><p>We have Staff engineers who own domains and ship them well. What we don't have is a single person accountable for whether those domains add up to a coherent platform and for whether the bets we're placing now still look right in five years. That's this role.</p><h2>You Will:</h2><ul><li><p><strong>The multi-year platform architecture.</strong> Ingestion, streaming, orchestration, transformation, and serving as one system rather than five. You decide what we build, what we buy, what we deprecate, and in what order.</p></li><li><p><strong>The streaming bet.</strong> Whether Kafka to Flink to BigQuery stays an analytics pipeline or becomes production infrastructure, and what that commits us to operationally, financially, and organizationally. You are the architect of the answer you choose.</p></li><li><p><strong>The contracts between organizations.</strong> The interfaces, service boundaries, and data contracts govern how other teams consume from and write into the platform. Where your standards end and another org's autonomy begins is a boundary you define with the VP of Data, not one handed to you.</p></li><li><p><strong>What 'trustworthy data' means here, and who is on the hook for it.</strong> You define the quality and freshness guarantees the platform makes, the tiering that determines which datasets get them, and the accountability model when they're missed. Staff engineers build the detection, validation, and alerting systems. You decide what we promise, to whom, and at what cost.</p></li><li><p><strong>The economics of the platform.</strong> The design decisions that determine what data costs us at scale (storage and compute strategy, reservation model, orchestration footprint) and the accountability framework that keeps consumption honest as more teams build on it. You set the framework. You don't tune every query.</p></li><li><p><strong>The self service strategy.</strong> What capabilities let Analytics Engineering and Data Science move without waiting on DPE, what guardrails keep that from breaking production, and how the platform stops being a bottleneck as demand grows faster than headcount.</p></li><li><p><strong>The standards the discipline runs on.</strong> Testing, CI/CD, observability, schema governance, and infrastructure as code practice, adopted by teams that don't report to you because the standards are good rather than because you can compel them.</p></li><li><p><strong>Architecture Review.</strong> You chair it, and you are the decision-maker of record for cross-team, multi-system, and cost-impacting changes, including ones that touch systems you don't own.</p></li><li><p><strong>The seams between data and everything else.</strong> ML and Data Science readiness, HIPAA and PHI compliance posture with Legal and Security, and infrastructure hardening with DevOps. Nobody else is looking at all four at once.</p></li><li><p><strong>The written record.</strong> ADRs, design docs, and RFCs that other teams cite as the reference. If a decision only exists in your head, you haven't finished making it.</p></li><li><p><strong>The technical ceiling of the org.</strong> Mentorship, design review, and hands-on pairing that makes Staff and Senior engineers better. Part of how you'll measure your impact is the volume of decisions you no longer have to make yourself.</p></li><li><p><strong>You stay hands-on throughout.</strong> You write and review production code, and you're in the room for platform-level P1s, driving the systemic fix rather than owning the runbook. This is a technical authority role, not an advisory one.</p></li></ul><h2>You Have:</h2><ul><li><p>15+ years building and owning data platform architecture, with a record of decisions whose consequences you stayed to live with, ideally across multiple companies or multiple platform generations</p></li><li><p>Evidence you've set technical direction for organizations you didn't manage, and got adoption through credibility rather than reporting lines</p></li><li><p>Experience defining the edges of your own architectural authority. Ambiguity about where your mandate ends should not stall you</p></li><li><p>Deep GCP and BigQuery expertise, plus real operational fluency in AWS (our Airflow runs on EKS). Multicloud is the job here, not a bonus</p></li><li><p>Modern data stack at platform scale: governing dbt across teams, Airflow/Astronomer, Kafka/Confluent, Databricks/Spark, Fivetran, and reverse ETL or activation platforms such as Hightouch</p></li><li><p>Event streaming in production at scale, including Schema Registry, data contracts, consumer lag management, and delivery semantics along with what they actually cost. Bonus if you've personally made the analytics versus production streaming call</p></li><li><p>Data governance and compliance in a regulated environment: HIPAA and PHI handling, data classification, access controls, audit logging, and GDPR</p></li><li><p>Terraform or equivalent, and the conviction that infrastructure changes are software changes</p></li><li><p>Strong Python and SQL. You raise the bar on production pipeline code by reviewing it, not by talking about it</p></li><li><p>Writing that creates alignment across organizations. Your design docs are where decisions get made, not summaries of decisions already made elsewhere</p></li></ul><h2>Preferred Qualifications:</h2><ul><li><p>Databricks, Unity Catalog, and Delta Lake in production at scale</p></li><li><p>CDC patterns and Flink for real-time processing, particularly where streaming infrastructure served both analytics and production or model serving paths across multiple teams</p></li><li><p>PySpark and SparkSQL for large-scale batch and streaming workloads</p></li><li><p>A BigQuery to Databricks Lakehouse migration, or an equivalent warehouse migration you led end-to-end</p></li><li><p>MLOps partnership: model training pipelines, feature stores, experimentation infrastructure, or the data foundations behind AI-driven product features</p></li><li><p>Go or Python service development for Kafka producers and consumers</p></li><li><p>Direct-to-consumer healthcare or telehealth with HIPAA and GDPR obligations</p></li><li><p>SOX compliance controls in a data engineering context</p></li></ul><h2>Our Benefits (there are more but here are some highlights):</h2><ul><li><p>Competitive salary & equity compensation for full-time roles</p></li><li><p>Unlimited PTO, company holidays, and quarterly mental health days</p></li><li><p>Comprehensive health benefits including medical, dental & vision, and parental leave</p></li><li><p>Employee Stock Purchase Program (ESPP)</p></li><li><p>401k benefits with employer matching contribution</p></li><li><p>Offsite team retreats</p></li></ul><p>We are committed to building a workforce that reflects diverse perspectives and prioritizes ethics, wellness, and a strong sense of belonging. If you're excited about this role, we encourage you to apply—even if you're not sure if your background or experience is a perfect match.</p><p>Hims considers all qualified applicants for employment, including applicants with arrest or conviction records, in accordance with the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance, the California Fair Chance Act, and any similar state or local fair chance laws.</p><p>It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.</p><p>Hims & Hers is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, please contact us at <a href='mailto:[email protected]'><u>[email protected]</u></a> and describe the needed accommodation. Your privacy is important to us, and any information you share will only be used for the legitimate purpose of considering your request for accommodation. Hims & Hers gives consideration to all qualified applicants without regard to any protected status, including disability. Please do not send resumes to this email address.</p><p>To learn more about how we collect, use, retain, and disclose Personal Information, please visit our <a href='https://www.hims.com/global-candidate-privacy-statement'><u>Global Candidate Privacy Statement</u></a>.</p>

AL, AK, AZ, AR, CA, CO, CT, DE, FL, GA, HI, ID, IL, IN, IA, KS, KY, LA, ME, MD, MA, MI, MN, MS, MO, MT, NE, NV, NH, NJ, NM, NY, NC, ND, OH, OK, OR, PA, RI, SC, SD, TN, TX, UT, VT, VA, WA, DC, WV, WI, WY

Data

<p>Toast creates technology to help restaurants and local businesses succeed in a digital world, helping business owners operate, increase sales, engage customers, and keep employees happy.</p><p>As a Staff Data Scientist, you’ll lead the design and development of scalable ML systems for use cases such as menu recommendation, demand forecasting, offer targeting, and guest personalization. You will serve as a technical thought partner across teams, set best practices, and influence the roadmap for ML-driven products that support key business outcomes. Your work will directly shape strategic decisions and enhance customer experience at scale.</p><h2>A day in the life (Responsibilities)</h2> <ul><li>Own the full machine learning lifecycle—from problem framing and data exploration to modeling, deployment, and monitoring—for mission-critical initiatives.</li><li>Design and implement advanced ML and statistical models that improve product performance, operational efficiency, or customer insights.</li><li>Collaborate with engineers, product managers, and business stakeholders to define project scope, success metrics, and integration strategy.</li><li>Guide architectural decisions, set modeling standards, and champion best practices for experimentation, validation, and productionization.</li><li>Mentor other data scientists and raise the technical bar through design reviews, feedback, and sharing domain expertise.</li><li>Proactively identify areas where data science can create business value and lead cross-functional efforts to drive those opportunities forward.</li><li>Leverage cutting edge AI tools to enhance your development workflow, improve velocity, and help pioneer new approaches to building - contributing to a culture of innovation and productivity across the team.</li></ul> <h2>What you'll need to thrive (Requirements)</h2> <ul><li>7+ years of experience in data science with a proven track record of delivering production ML systems that drive measurable impact.</li><li>Deep knowledge of statistical modeling, machine learning (e.g., tree-based models, time series, deep learning), and model evaluation.</li><li>Experience working with real-world product data at scale and translating ambiguous problems into well-scoped ML solutions.</li><li>Experience with distributed data processing and training, real-time inference, and ML Ops frameworks</li><li>Prior experience mentoring other data scientists or acting as a tech lead.</li><li>Experience leading experimentation (e.g., A/B testing), causal inference, and real-time decision systems.</li><li>Proficiency in Python and SQL, and experience with ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow).</li><li>Strong grasp of software engineering principles including modular design, version control, testing, and CI/CD.</li><li>Hands-on experience with cloud platforms (preferably AWS), including tools like SageMaker, Athena, Glue, DynamoDB, and Bedrock.</li><li>Excellent communication skills and the ability to influence both technical and non-technical stakeholders.</li><li>Strong business acumen with the ability to align technical solutions with company goals.</li><li>Experience building services on top of LLMs in a large scale production environment.</li></ul> <h2>Bonus <em>ingredients*</em>:</h2> <ul><li>An advanced degree in Computer Science, Statistics, or a related STEM field is preferred.</li><li>Familiarity with MLOps tooling for monitoring, drift detection, retraining, and explainability.</li><li>Experience fine-tuning LLMs and applying reinforcement learning from human feedback (RLHF) to improve model performance and alignment.</li></ul> <h2>AI at Toast</h2> <p>At Toast, one of our company values is that we're hungry to build and learn. We believe learning new AI tools empowers us to build for our customers faster, more independently, and with higher quality. We provide these tools across all disciplines, from Engineering and Product to Sales and Support, and are inspired by how our Toasters are already driving real value with them. The people who thrive here are those who embrace changes that let us build more for our customers; it’s a core part of our culture.</p><p><strong>Our Total Rewards Philosophy <br></strong>We strive to provide competitive compensation and benefits programs that help to attract, retain, and motivate the best and brightest people in our industry. Our total rewards package goes beyond great earnings potential and provides the means to a healthy lifestyle with the flexibility to meet Toasters’ changing needs. Learn more about our benefits at <a href='https://careers.toasttab.com/toast-benefits'>https://careers.toasttab.com/toast-benefits</a>.</p><p>#LI-Remote</p><p>The base salary range for this role is listed below. The starting salary will be determined based on skills, experience, and geographic location. In addition to base salary, our total rewards components include cash compensation (overtime, bonus/commissions if eligible), equity, and benefits. You can learn more about how we align pay with local labor markets in our <a href='https://careers.toasttab.com/us-pay-zones'>Geographic Pay Zone Philosophy</a>.</p><p>Zone A</p><p>$170,000&mdash;$272,000 USD</p><p>Zone B</p><p>$148,000&mdash;$237,000 USD</p><p>Zone C</p><p>$133,000&mdash;$213,000 USD</p><p><h2>How Toast Uses AI in its Hiring Process</h2> <p>Throughout the hiring process, our goal is to get to know you. We use AI tools to support our recruiters and interviewers with tasks like note-taking, summarization, and documentation of interviews to ensure they can be fully focused on your conversation. All hiring decisions are made by people. To learn more: <a href='https://careers.toasttab.com/ai-in-hiring'>https://careers.toasttab.com/ai-in-hiring</a></p><p><strong>Our Approach to Hybrid Working</strong><br><br>We embrace a hybrid work model that fosters in-person collaboration while valuing individual needs. Our goal is to build a strong culture of connection as we work together to empower the hospitality community, regardless of location. Please visit the Locations page on our career site to learn more about our in-office expectations by region: <a href='https://careers.toasttab.com/locations-toast'>https://careers.toasttab.com/locations-toast</a></p><h2>Diversity, Equity, and Inclusion is Baked into our Recipe for Success</h2> <p>At Toast, our employees are our secret ingredient—when they thrive, we thrive. The restaurant industry is one of the most diverse, and we embrace that diversity with authenticity, inclusivity, respect, and humility. By embedding these principles into our culture and design, we create equitable opportunities for all and raise the bar in delivering exceptional experiences.</p><h2>We Thrive Together</h2> <p>We embrace a hybrid work model that fosters in-person collaboration while valuing individual needs. Our goal is to build a strong culture of connection as we work together to empower the restaurant community. To learn more about how we work globally and regionally, check out: <a href='https://careers.toasttab.com/locations-toast'>https://careers.toasttab.com/locations-toast</a>.</p><h2>Apply today!</h2> <p>Toast is committed to creating an accessible and inclusive hiring process. As part of this commitment, we strive to provide reasonable accommodations for persons with disabilities to enable them to access the hiring process. If you need an accommodation to access the job application or interview process, please contact <a href='mailto:[email protected]'>[email protected]</a>.</p><p><em>------</em></p><p><em>For roles in the United States, it is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.</em></p>

AL, AK, AZ, AR, CA, CO, CT, DE, FL, GA, HI, ID, IL, IN, IA, KS, KY, LA, ME, MD, MA, MI, MN, MS, MO, MT, NE, NV, NH, NJ, NM, NY, NC, ND, OH, OK, OR, PA, RI, SC, SD, TN, TX, UT, VT, VA, WA, DC, WV, WI, WY

Data

<p>At Vanta, our mission is to help businesses earn and prove trust.<strong> </strong>We believe that security should be monitored and verified continuously, and we empower companies to practice better security and prove it with ease. Vanta has a kind and talented team, and while some have prior security experience, many have been successful at Vanta without it. </p><p>As a Senior Data Analyst on the Finance team, you’ll play a pivotal role in uncovering the insights that shape company-wide planning, forecasting, and strategic decision-making. This high-impact role blends analytical rigor, technical fluency, and business acumen to steer strategy and identify opportunities for scalable growth.</p><p>The Finance Data team partners with both Finance and other teams across Vanta. You’ll collaborate closely with stakeholders to build trust and deliver data-driven recommendations; your work will influence everything from operating plans and investment decisions to self-serve reporting and process automation. This is a unique opportunity to deepen your analytics expertise in a dynamic, high-growth environment, with visibility into executive-level priorities and the ability to shape them with data.</p><h2>What you’ll do as a Senior Data Analyst at Vanta:</h2><ul><li><p>Deliver strategic insights by conducting deep, prioritized analyses that inform high-impact financial decisions.</p></li><li><p>Act as a technical partner to teams across FP&A, Accounting, RevOps, Product, Marketing, and more.</p></li><li><p>Increase team efficiency by automating recurring deliverables and helping scale workflows as the company grows.</p></li><li><p>Empower decision-makers with self-service dashboards and data assets that surface trends and drive informed choices across the business.</p></li><li><p>Advance our analytics infrastructure by partnering with Data Engineering and other analytics teams to democratize access to high quality data and insights.</p></li></ul><h2>How to be successful in this role:</h2><ul><li><p>Experience: 4+ years of experience in data analysis or equivalent function. Exposure to FP&A, Accounting, or SaaS metrics is a plus.</p></li><li><p>Technical Skills: Strong proficiency in SQL and data visualization tools (e.g., Tableau, Sigma), with experience handling large and complex data sets. Familiarity with DBT is preferred. Bonus points for skill in Python for advanced analysis.</p></li><li><p>Analytical Thinking: Proven ability to analyze complex data sets, uncover key insights, and translate findings into actionable strategies that drive financial outcomes.</p></li><li><p>Collaboration: Demonstrated success working cross-functionally and building relationships across business teams. Comfortable engaging stakeholders with varying levels of data fluency.</p></li><li><p>Communication: Clear and effective communicator, both written and verbal. Skilled at presenting complex data insights to non-technical audiences.</p></li><li><p>Education: Bachelor’s degree in Data Analytics, Statistics, Informatics, Finance, Economics, Business, or a related field.</p></li><li><p>Must be authorized to work in the U.S. without the need for current or future employer sponsorship.</p></li><li><p>Open to using AI to amplify their skills and strengthen their work - demonstrating curiosity, a willingness to learn, and sound judgment in applying AI responsibly to improve efficiency and impact.</p></li></ul><h2>What you can expect as a Vanta’n:</h2><ul><li><p>Industry-competitive salary and equity</p></li><li><p>Comprehensive medical, dental, and vision coverage, with 100% of employee-only benefit premiums covered for most medical plans</p></li><li><p>16 weeks paid Parental Leave for all new parents</p></li><li><p>Health & wellness stipend</p></li><li><p>Remote workspace, internet, and cellphone stipend</p></li><li><p>Commuter benefits for team members who report to the SF and NYC office</p></li><li><p>Family planning benefits</p></li><li><p>Matching 401(k) contribution with immediate vesting</p></li><li><p>Flexible PTO policy, plus 80 hours of Sick Time</p></li><li><p>11 company-paid holidays</p></li><li><p>Virtual team building activities, lunch and learns, and other company-wide events!</p></li><li><p>Offices in SF, NYC, London, Dublin, Tel Aviv, and Sydney</p></li></ul><p>To provide greater transparency to candidates, we share base pay ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar-stage growth companies. Final offer amounts are determined by multiple factors and may vary based on candidate location, skills, depth of work experience, and relevant licenses/credentials. </p><p>#LI-remote</p><p><em>At Vanta, we are committed to hiring diverse talent of different backgrounds and as such, it is important to us to provide an inclusive work environment for all. We do not discriminate on the basis of race, gender identity, age, religion, sexual orientation, veteran or disability status, or any other protected class. As an equal opportunity employer, we encourage and welcome people of all backgrounds to apply.</em></p><h2>About Vanta</h2><p>We started in 2018, in the wake of several high-profile data breaches. Online security was only becoming more important, but we knew firsthand how hard it could be for fast-growing companies to invest the time and manpower it takes to build a solid security foundation. Vanta was inspired by a vision to restore trust in internet businesses by enabling companies to improve and prove their security. From our early days automating security monitoring for compliance standards like SOC 2, HIPAA and ISO 27001 to creating the world's leading Trust Management Platform, our vision remains unchanged. </p><p>Now more than ever, making security continuous—not just a point-in-time check— is essential. Thousands of companies rely on Vanta to build, maintain and demonstrate their trust— all in a way that's real-time and transparent.</p><h2>Referral Instructions</h2><p>If you are being referred for the role, please contact that person to apply on your behalf.</p>

AL, AK, AZ, AR, CA, CO, CT, DE, FL, GA, HI, ID, IL, IN, IA, KS, KY, LA, ME, MD, MA, MI, MN, MS, MO, MT, NE, NV, NH, NJ, NM, NY, NC, ND, OH, OK, OR, PA, RI, SC, SD, TN, TX, UT, VT, VA, WA, DC, WV, WI, WY

Data

<p><a href='https://www.sentilink.com/'><u>SentiLink</u></a> stops more than 150,000 fraud attempts and verifies more than 3 million identities every day to protect both institutions and consumers. The problems we work on are challenging, and solving them takes deep domain expertise, rigorous analysis, and a willingness to dig into the details.</p><p>At SentiLink, you'll work alongside smart, highly collaborative colleagues who respect each other's time and judgment, take ownership, and follow through on their commitments. Together, we do truly meaningful work protecting the identities of innocent consumers and flagging the fraudsters attempting to exploit them.</p><p>We're well capitalized and growing quickly. We already serve 13 of the top 15 U.S. banks, we're expanding into new markets, and we're backed by Craft Ventures, Andreessen Horowitz, NYCA, and Max Levchin. We've been named to the<a href='https://www.forbes.com/companies/sentilink/?list=fintech50'> <u>Forbes Fintech 50</u></a> and as a<a href='https://www.businesswire.com/news/home/20260330439998/en/SentiLink-Named-a-2026-FICO-Industry-Vanguard-Decision-Award-Winner-for-Leadership-in-Identity-Theft-Detection'> <u>2026 FICO Industry Vanguard Decision Award Winner</u></a>. We were also the<a href='https://resources.sentilink.com/blog/sentilink-makes-history-as-first-ecbsv-provider'> <u>first company to go live</u></a> with the electronic Consent Based Social Security Number Verification (eCBSV) service, and we've <a href='https://resources.sentilink.com/media/dr.-david-maimons-congressional-testimony-on-emerging-fraud-threats-and-the-evolving-fraud-landscape'><u>testified before the U.S. Congress</u></a> on the future of identity.</p><p>We want SentiLink to be the best place you've ever worked. We offer generous benefits and support a range of working arrangements, from fully remote to in-office. We are a digital-first company with strong collaboration across the U.S. and India, and we meet in person regularly to build relationships. We have offices in Austin, San Francisco, New York City, Seattle (Bellevue), Los Angeles, and Chicago in the U.S., and in Gurugram (Delhi) and Bengaluru in India.</p><h2>Role:</h2><p>As a Data Science Manager for Application Fraud at SentiLink, you will directly manage a team of talented data scientists that build our suite of products: models that identify fraudsters and also advance our growing suite of products in financial risk. In this capacity, you will be relied upon to be a technical leader, mentor, and owner of your respective domain, both for your own team and the organization. Utilize your abilities as a strong data scientist to mentor your team, probe their understanding and challenge them to do their best work. Your team will often work on projects with high visibility and impact that require deep domain understanding, critical thinking and strong technical abilities. This role requires managing full-stack data scientists, whose work involves model development, analysis, and writing production code. You yourself should share that same skillset and be interested in having end-to-end ownership in a fast-moving environment where deep domain understanding drives development and unusual insights drive our competitive advantage rather than optimization of new machine learning methodologies.</p><p><strong>Technologies: </strong>Python 3, PostgreSQL, and AWS infrastructure (EC2, S3, RDS, Redshift, etc.)</p><h2>Responsibilities:</h2><ul><li><p>Directly manage a team of highly skilled data scientists. Start from 2-3 and grow to 5-6.</p></li><li><p>Act as a technical mentor that can dive deep and provide detailed direction.</p></li><li><p>Lead planning, resourcing and communications with senior leadership, product and engineering teams.</p></li><li><p>Develop strong business intuition and guide your team to deliver performant DS solutions on aggressive timelines.</p></li><li><p>Develop and maintain SentiLink’s fraud detection models through the full model development lifespan: from data acquisition decisions through featurization, focusing labeling resources, model training, experimentation, productionalization, and monitoring.</p></li><li><p>Research new types of fraud and develop new SentiLink products around identity verification.</p></li><li><p>Achieve success by researching / developing through iteration, integration of new data sources and inventive feature engineering.</p></li><li><p>Write production-ready code that can be relied on for real-time decision making by our partners.</p></li><li><p>Design, perform, and present analyses that will inform data acquisition, product development, risk operations priorities, marketing, and sales efforts.</p></li></ul><h2>Requirements:</h2><ul><li><p>10+ years relevant work experience & relevant Masters or 7+ years & relevant PhD.</p></li><li><p>2-5 years experience directly managing a team of data scientists, ideally in a startup environment.</p></li><li><p>3+ years of startup experience.</p></li><li><p>Excellent communicator and team player.</p></li><li><p>Proven track record of solving complex / high profile business problems with DS / ML solutions.</p></li><li><p>Experience in communicating outcomes / progress to senior management / stakeholders.</p></li><li><p>Very strong in “end to end” DS development: Planning, fleshing out success criteria / metrics, getting buy-in, developing the solution, delivering the solution (prod / deck / strategy doc / etc).</p></li><li><p>Strong practical ML / Stats knowledge, i.e. can easily employ the suite of standard ML / stats tools to quickly scope out solutions, and double down where needed. Experience with SOTA ML solutions is a plus.</p></li><li><p>Interest in developing deep domain expertise for product-focused work: a background in fraud is not required, but willingness to learn is.</p></li><li><p>Experience writing production code and tests.</p></li><li><p>Detail oriented and thoughtful—someone we can rely on to make business-changing decisions.</p></li><li><p>Thrive in a fast paced environment characterized by the need to solve extremely varied, high impact, open ended problems.</p></li><li><p>Bonus for familiarity with: identity solutions, fintech, or adjacent industries.</p></li><li><p>Candidates must be legally authorized to work in the United States and must live in the United States.</p></li></ul><h2>Compensation:</h2><p>$210,000-$260,000/year + equity + benefits</p><h2>Perks:</h2><ul><li><p>Employer paid group health insurance for you and your dependents</p></li><li><p>401(k) plan with employer match (or equivalent for non US-based roles)</p></li><li><p>Flexible paid time off</p></li><li><p>Regular company-wide in-person events</p></li><li><p>Home office stipend, and more!</p></li></ul><h2>Corporate Values:</h2><ul><li><p>Follow Through</p></li><li><p>Deep Understanding</p></li><li><p>Whatever It Takes</p></li><li><p>Do Something Smart</p></li></ul>

AL, AK, AZ, AR, CA, CO, CT, DE, FL, GA, HI, ID, IL, IN, IA, KS, KY, LA, ME, MD, MA, MI, MN, MS, MO, MT, NE, NV, NH, NJ, NM, NY, NC, ND, OH, OK, OR, PA, RI, SC, SD, TN, TX, UT, VT, VA, WA, DC, WV, WI, WY

Data

<h2>Senior Data Scientist</h2><h2>About Nash</h2><p>Nash is the autonomic logistics platform. We unify decisioning and execution across fleets, carriers, providers, and fulfillment networks, continuously adapting as conditions change and pursuing the best possible outcome for each business.</p><p>The world’s largest retailers, grocers, and pharmacies, including Walmart, 7-Eleven, Woolworths, and Coles, run critical logistics workflows on Nash. Your work will influence real-world decisions across millions of deliveries.</p><p>Nash was founded in 2021 by Mahmoud Ghulman and Aziz Alghunaim. We are backed by Y Combinator, a16z, OpenAI, and other leading investors, and headquartered in San Francisco.</p><h2>About the role</h2><p>We are hiring Nash’s first Data Scientist. You will combine product judgment, logistics or marketplace expertise, and pragmatic machine learning skills to build data products from discovery through production and measurement.</p><p>You will work across pricing, dispatch, carrier selection, ETA prediction, routing, and supply-demand forecasting. This is a high-ownership role for someone who can find valuable problems, turn ambiguity into measurable outcomes, and build the models and systems needed to improve those outcomes in production.</p><p>You will partner directly with Product, Engineering, Operations, customers, and company leadership.</p><h2>What you’ll do</h2><ul><li><p>Identify and scope high-impact opportunities across pricing, cost prediction, dispatch, carrier selection, ETA prediction, routing, and marketplace balancing.</p></li><li><p>Own data science initiatives from 0→1 discovery through 1→10 iteration, deployment, and performance improvement.</p></li><li><p>Work with large, messy operational datasets, including delivery events, geospatial data, carrier performance, customer constraints, and SLA outcomes.</p></li><li><p>Build models that account for real-world logistics constraints, shifting demand, provider availability, and service requirements.</p></li><li><p>Develop production data pipelines and model integrations using Python, SQL, and Snowflake.</p></li><li><p>Partner with engineers to serve models through APIs, batch pipelines, or real-time decision systems.</p></li><li><p>Establish evaluation frameworks, monitoring, experimentation, and A/B testing practices.</p></li><li><p>Measure model performance against business outcomes such as cost, reliability, on-time delivery, and operational intervention.</p></li><li><p>Work directly with enterprise customers to understand their operations and convert business requirements into technical approaches.</p></li><li><p>Communicate findings, tradeoffs, and recommendations clearly to technical and non-technical audiences.</p></li></ul><h2>What you’ll bring</h2><ul><li><p>4+ years of experience as a Data Scientist, Machine Learning Engineer, or in a related quantitative role.</p></li><li><p>Experience in logistics, marketplaces, supply chain, operations research, or another domain with complex real-world constraints.</p></li><li><p>A record of independently taking data science projects from problem definition through production and measurement.</p></li><li><p>Strong proficiency in Python and SQL, with experience working in cloud data warehouses. Snowflake experience is preferred.</p></li><li><p>Experience building and maintaining production machine learning systems. Deep MLOps specialization is not required.</p></li><li><p>Strong product judgment and the ability to connect modeling decisions to customer and business outcomes.</p></li><li><p>Comfort working with incomplete data, ambiguous questions, and changing operational conditions.</p></li><li><p>Clear written and verbal communication, including experience working with customers or senior stakeholders.</p></li><li><p>High agency in a fast-moving environment. You notice valuable problems and act on them.</p></li></ul><h2>Bonus</h2><ul><li><p>Experience with routing, ETA modeling, optimization algorithms, or geospatial data.</p></li><li><p>Familiarity with dispatch systems, carrier networks, logistics marketplaces, or pricing models.</p></li><li><p>Experience with supply-demand forecasting or marketplace balancing.</p></li><li><p>Exposure to dbt, Airflow, or related data orchestration tools.</p></li><li><p>Experience deploying models through APIs or real-time decision systems.</p></li><li><p>Prior experience at an early-stage company or in a founding data role.</p></li></ul><h2>Why this role matters</h2><p>The decisions Nash makes affect what a delivery costs, which resource handles it, when it arrives, and whether the customer’s promise holds when conditions change.</p><p>As our first Data Scientist, you will define how Nash uses operational data to make those decisions sharper. The models you build will move quickly from analysis into live logistics workflows, giving you a direct view into their customer and business impact.</p><h2>What you’ll love about Nash</h2><ul><li><p>An early-stage, well-funded company with real revenue and global enterprise customers</p></li><li><p>Significant ownership and autonomy, with direct collaboration with the founders</p></li><li><p>Quarterly team onsites to connect and align in person</p></li><li><p>Competitive compensation and meaningful equity</p></li><li><p>Flexible paid time off</p></li><li><p>Health, dental, and vision insurance</p></li></ul><h2>Equal opportunity</h2><p>At Nash, we believe diverse teams are the strongest teams. We invite applicants of all genders, races, ethnicities, nationalities, ages, religions, sexual orientations, disability statuses, educational experiences, family situations, and socioeconomic backgrounds.</p><p><strong>More about </strong><a href='http://Nash.AI'><strong>Nash</strong></a></p><h3>Nash is the platform that powers modern logistics.</h3><p>Commerce has inverted. For decades, customers came to where products and services were. Now products and services come to them, on their terms, in real time. That shift has turned every company into a logistics company, even though almost none of them were built to be one. Couriers, fleets, gig workers, parcel carriers, in-store labor, and increasingly autonomous systems all have to be coordinated in real time, against tighter windows and rising expectations, with hard-fought customer trust on the line.</p><p>Nash unifies decisioning, execution, and capacity into a single programmable platform. Real-time, AI-native intelligence determines what should happen, operational control executes it, and the platform dynamically orchestrates capacity from any source: a company's own fleets, partners, or the Nash delivery network. Whether a job involves a courier, a gig driver, an internal fleet, a store employee, a technician, or an autonomous vehicle, Nash selects the right resource and manages execution through completion.</p><p>We power delivery and logistics for some of the most recognizable brands in commerce, including Walmart, Urban Outfitters, 7-Eleven, and Woolworths, alongside platforms like Shopify and Toast. Over the next decade, logistics will become as foundational to commerce as payments, cloud, and connectivity. Nash is the platform that powers it.</p><p>Nash was founded in 2021 by Mahmoud Ghulman (2x Founder, MIT) and Aziz Alghunaim (2x Founder, 2x YC, Ex-Palantir, MIT) and is backed by Y Combinator, a16z, and other top investors. We are headquartered in San Francisco.</p><h3>What You’ll Love About Us</h3><p>✅ Early-stage, well-funded startup – directly impact the company and grow your career!<br>✅ Quarterly broader team on-sites to bond with teammates<br>✅ Competitive compensation and opportunity for equity<br>✅ Flexible paid time off<br>✅ Health, dental, and vision insurance for US employees</p>

AL, AK, AZ, AR, CA, CO, CT, DE, FL, GA, HI, ID, IL, IN, IA, KS, KY, LA, ME, MD, MA, MI, MN, MS, MO, MT, NE, NV, NH, NJ, NM, NY, NC, ND, OH, OK, OR, PA, RI, SC, SD, TN, TX, UT, VT, VA, WA, DC, WV, WI, WY

Data

<p><em>Superhuman offers a dynamic hybrid working model for this role. This flexible approach gives team members the best of both worlds: plenty of focus time along with in-person collaboration that helps foster trust, innovation, and a strong team culture.</em></p><p><em>Preferred locations for team members for our Data Platform roles are our San Francisco or Seattle hubs.</em></p><h2>About Superhuman</h2><p>Grammarly is now part of Superhuman, the AI productivity platform on a mission to unlock the superhuman potential in everyone. The Superhuman suite of apps and agents brings AI wherever people work, integrating with over 1 million applications and websites. The company's products include Grammarly's writing assistance, Docs’ collaborative workspace, Mail's inbox management, and Go, the proactive AI assistant that understands context and delivers help automatically. Founded in 2009, Superhuman empowers over 40 million people, 50,000 organizations, and 3,000 educational institutions worldwide to eliminate busywork and focus on what matters. Learn more at <a href='http://superhuman.com'>superhuman.com</a> and about our values <a href='https://superhuman.com/company/values'>here</a>.</p><h2>The Opportunity</h2><p>To achieve our ambitious goals, we’re looking for a <strong>Data Engineer</strong> to join our <strong>Data Foundations </strong>team and help us build a world-class data platform. Superhuman’s success depends on its ability to efficiently ingest and process over 70 billion daily events to improve our products. This role presents a unique opportunity to experience all aspects of building complex data pipelines and systems, including contributing to the strategy, defining the architecture, and developing and shipping to production.</p><p>Superhuman is a compound startup: we build many products as one integrated suite rather than standalone tools. That model creates an unusually rich data opportunity, with signals spanning our full product suite across both consumers and enterprises — and the foundational data you build connects those surfaces.</p><p>The Data Foundations team is part of the Data Platform org, powering data needs across Superhuman rather than a single product surface. It owns the foundational datasets and data models that define the fundamental entities of Superhuman's business, serving as building blocks for the company's other data teams and data scientists. Behind the scenes, the team develops and runs large-scale ETL pipelines that process petabytes of data and billions of events daily.</p><p>This is a high-impact role at the intersection of data engineering, data-intensive applications, and data modeling, where the systems you build directly shape how efficiently our other Data teams can build their datasets.</p><p><strong>What you’ll do</strong></p><p>As a Data Engineer on the Data Foundations team, you will design and implement robust, scalable, and reliable data pipelines and systems that handle large volumes of data, empowering both product features and data-driven decision-making across the company. Your work will span areas such as ETL data pipelines, data lakes, performance-oriented data processing, and ETL framework development.</p><ul><li><p>Architect, build, and own large-scale data pipelines and data lakes (Spark/Databricks) that ingest and process billions of daily events into reliable, decision-grade datasets.</p></li><li><p>Design and implement solutions that keep data available, secure, and scalable across the platform, enabling both real-time and batch processing.</p></li><li><p>Own data quality, freshness, and reliability for the foundational datasets other teams depend on, with automated checks, monitoring, and alerting.</p></li><li><p>Build the ETL frameworks and tooling that let other Data teams and data scientists self-serve and model core business entities into clean, well-documented, reusable datasets.</p></li><li><p>Partner with product teams, back-end engineers, ML engineers, and Data Science to turn business questions into high-impact data products behind business-critical features, research, and experimentation.</p></li><li><p>Collaborate with leadership to shape the team’s charter and technical roadmap.</p></li></ul><h2>Qualifications</h2><ul><li><p>You have 3+ years of experience running live production environments, including high-load or data-intensive workflows, with a focus on uptime and reliability.</p></li><li><p>You’re proficient in SQL and Python, with deep hands-on experience in Spark and a modern lakehouse or cloud data warehouse (Databricks, Delta Lake, dbt, Snowflake, or similar).</p></li><li><p>You have strong knowledge of ETL/ELT design patterns, orchestration tools (e.g., Airflow, dbt, or Dagster), data quality frameworks, and CI/CD for data with Git-based deployments.</p></li><li><p>You have data modeling and data warehouse design skills, along with a rigorous approach to data quality and observability.</p></li><li><p>You have hands-on experience with modern data storage technologies (for example, Delta Lake, Snowflake, BigQuery, or Redshift).</p></li><li><p>You communicate clearly and collaborate well across diverse teams and stakeholders, turning business needs into robust data solutions and trustworthy metrics.</p></li><li><p>You bring a strong ownership mindset, taking end-to-end responsibility for the systems you build, from strategy and architecture through production and ongoing reliability.</p></li><li><p>You have a strong acumen for scalable, highly complex data processing, think holistically about problems, and raise the bar on your team’s craft.</p></li><li><p>You’re a self-starting problem-solver who thinks from first principles, manages priorities across multiple projects, and thrives in a fast-paced, results-driven environment.</p></li></ul><h3>Nice to have</h3><ul><li><p>You have experience operating large-scale distributed systems, as well as in data engineering and data modeling.</p></li><li><p>Experience with high-throughput, real-time streaming systems (for example, Kafka, Flink, or Spark Structured Streaming) at the scale of billions of events per day.</p></li><li><p>Comfort with data lake and lakehouse technologies (for example, Delta Lake, Iceberg, or Hudi) and managing cloud infrastructure as code (for example, Terraform).</p></li><li><p>A track record of building self-serve data products, tools, or frameworks that other teams rely on.</p></li><li><p>Experience partnering with analytics, data science, or machine learning teams as a strategic data partner to productionize data and models.</p></li></ul><h2>Compensation and Benefits</h2><p>Superhuman offers all team members competitive pay along with a benefits package encompassing the following and more:</p><ul><li><p>Excellent health care (including a wide range of medical, dental, vision, mental health, and fertility benefits)</p></li><li><p>Disability and life insurance options</p></li><li><p>401(k) matching</p></li><li><p>Paid parental leave</p></li><li><p>20 days of paid time off per year, 12 days of paid holidays per year, two floating holidays per year, and flexible sick time</p></li><li><p>Generous stipends (including those for caregiving, pet care, wellness, your home office, and more)</p></li><li><p>Annual professional development budget and opportunities</p></li></ul><p>Superhuman takes a market-based approach to compensation, which means base pay may vary depending on your location. Our US locations are categorized into two compensation zones based on proximity to our hub locations.</p><p>Base pay may vary considerably depending on job-related knowledge, skills, and experience. The expected salary ranges for this position are outlined below by compensation zone and may be modified in the future.</p><h3>US Zone 1</h3><p>175,000 to 245,000</p><h3>US Zone 2</h3><p>157,000 to 220,500</p><h3></h3><h2>We encourage you to apply</h2><p>At Superhuman, we value our differences, and we encourage all to apply—especially those whose identities are traditionally underrepresented in tech organizations. We do not discriminate on the basis of race, religion, color, gender expression or identity, sexual orientation, ancestry, national origin, citizenship, age, marital status, veteran status, disability status, political belief, or any other characteristic protected by law. Superhuman is an equal opportunity employer and a participant in the US federal E-Verify program (US). We also abide by the Employment Equity Act (Canada).</p>

CA, WA

Data

<p>We're hiring a Data Scientist II on our Soccer team to develop the statistical and machine learning models our partner clubs use for player recruitment. I'm Jacob Mortensen, Senior Manager, Data Science at Teamworks. Our team primarily focuses on building models using both player tracking data and event data to identify undervalued players and characterize the skills that make them effective. The work supports high-stakes recruitment decisions for professional clubs across global football.</p><p>The team is managing growing demand from partner clubs alongside model maintenance and new development. This hire will take ownership across the model lifecycle, from design and validation through deployment and improvement. That added capacity will help us move important initiatives forward while keeping our existing models accurate and reliable.</p><h2>The Role</h2><ul><li><p>Develop statistical and machine learning models that help professional soccer clubs identify undervalued players and strong recruitment targets</p></li><li><p>Use player tracking data to build spatio-temporal models that quantify player impact and skill</p></li><li><p>Build metrics and analyses that soccer teams rely on to make decisions, and support client-facing work by building tools to support model interpretation and understanding</p></li><li><p>Validate models and outputs — your own and others’ — with enough rigor that the team can trust what ships</p></li><li><p>Write clear reports that communicate technical work to clients</p></li><li><p>Partner with our engineering team to deploy models on cloud infrastructure and turn strong analytical work into reliable production systems</p></li><li><p>Review code from other data scientists, share constructive feedback, and contribute ideas that advance the team's work</p></li></ul><h2>What I'm Looking For</h2><h3>What You Must Bring</h3><ul><li><p>3+ years of professional or research experience writing code in R or Python for data science, statistics, or machine learning work</p></li><li><p>Comfort with SQL for building and querying structured data</p></li><li><p>Strong data science fundamentals: you understand how models work, what they need from the data, and how to set data up to support them</p></li><li><p>Experience working with sports tracking data, including understanding the kinds of models typically built and the data challenges that come with them</p></li><li><p>Strong communication skills — you'll be explaining modeling decisions directly to partner clubs, not just internal teammates</p></li></ul><h3>Even Better If</h3><ul><li><p>You have direct experience with soccer data or soccer analytics (inside a team, public work, or academically)</p></li><li><p>You have a demonstrated track record of tackling hard problems through published research, blog posts, conference talks, or public projects</p></li><li><p>Experience using a cloud compute provider (e.g. AWS or Google Cloud) to train and deploy models</p></li><li><p>Comfort using AI coding tools, paired with the judgment to recognize when their output needs to be questioned or corrected</p></li></ul><h2>Why This Role</h2><p>Soccer analytics is moving quickly, and this team is helping shape how advanced modeling is used in recruitment. You'll have meaningful ownership, room to develop new approaches, and the opportunity to see your work used by professional clubs. You'll also help define how the team builds, maintains, and scales its model portfolio as demand grows.</p><p><em>This role is not eligible for sponsorship at this time.</em></p><p><br><em>To all recruitment agencies: Teamworks does not accept agency resumes. Please do not forward resumes to our jobs alias, Teamworks employees or any other organization location. Teamworks is not responsible for any fees related to unsolicited resumes.</em></p><h2>About Teamworks</h2><p>We're the Operating System for Sports™, powering 7,000+ organizations worldwide, from collegiate programs to every major pro league. Founded in 2006, we've evolved from a messaging tool for college football into the leading sports tech platform, with 600+ global teammates building the future of sports tech. Our solutions span Personnel, Coaching, Performance, Operations, and Intelligence - helping teams recruit smarter, train better, stay compliant, and win.<br><br>Teamworks is an equal opportunity employer - if you live our core values every day and are honest, hardworking, humble, committed, innovative, and an all-around exceptional person, you'll thrive at Teamworks. We are committed to building a diverse and inclusive workforce and take affirmative action to not discriminate based on race, religion, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, age, sexual orientation, veteran or military status, or any other legally protected characteristics. This policy applies to all employment practices within our organization, including but not limited to recruiting, hiring, promotion, termination, compensation, benefits, and training. Teamworks is committed to providing reasonable accommodations for candidates with disabilities who need assistance during the hiring process. To request a reasonable accommodation, please email <a href='mailto:[email protected]'><u>[email protected]</u></a>.</p>

AL, AK, AZ, AR, CA, CO, CT, DE, FL, GA, HI, ID, IL, IN, IA, KS, KY, LA, ME, MD, MA, MI, MN, MS, MO, MT, NE, NV, NH, NJ, NM, NY, NC, ND, OH, OK, OR, PA, RI, SC, SD, TN, TX, UT, VT, VA, WA, DC, WV, WI, WY

Data

<h2>About the role</h2><p><br>This is an ideal opportunity for a highly motivated individual to get in on the ground floor as we build out our Professional Services and Managed Services functions at Cyberhaven. The Senior Data Protection Analyst holds a key position in providing continuous value for our customers and is responsible for advancing the mission of identifying potential insider threats and investigating endpoint forensic incidents. You will be responsible for performing technical analysis of data security incidents, finding and exposing risk in a customers environment as well as handling documentation and project management aspects of incident response. You will also perform analysis of events and incidents.</p><p><br><strong>What you’ll do</strong></p><ul><li><p>Provide insight into DLP analytics and related issues.</p></li><li><p>Analyze Cyberhaven’s Data Detection and Response (DDR) platform event data to improve policies and incidents/alerts and bring focus to areas where data loss risk may exist.</p></li><li><p>Refine datasets and policies and manage them as customers’ data risk strategy matures and business needs evolve.</p></li><li><p>Prepare and present summaries and reports to internal team members.</p></li><li><p>Eliminate noise and false-positive information from analytic results to enhance detection accuracy.</p></li><li><p>Conduct forensic analysis on people, groups, and non sanctioned egress destinations as requested.</p></li></ul><h2>Who you are</h2><ul><li><p>5+ years with data protection or adjacent security tools (EDR, SIEM, SOAR) and 2+ years in Insider Threat/InfoSec.</p></li><li><p>Strong grasp of endpoint protection best practices and incident mitigation workflows.</p></li><li><p>Experience with DLP, Insider Threat, CASB and controls for handling sensitive data.</p></li><li><p>Comfortable across macOS, Linux, Windows and cloud platforms (AWS, GCP, Azure).</p></li><li><p>Data & automation: SQL for analysis; build/maintain dashboards; edit XML-based DLP rules; script and use APIs.</p></li><li><p>Excellent problem-solving and communication skills; collaborative on a global team; customer-centric with a passion for cloud security and emerging tech.</p></li></ul><p>Joining Cyberhaven means joining the team building Data Security for the Agentic Enterprise. Traditional tools fall short. Cyberhaven traces the full lifecycle of your data, adapting protection to changing context, so protection moves with the way people actually work, not against it. AI Changed Work. We Protect It.<br>Backed by $250M from leading investors like Khosla and Redpoint, our team includes leaders who built industry-defining technologies at CrowdStrike, Palo Alto Networks, Meta, Google, and more. This role lets you shape the future of data security, working alongside people driven to protect workflows, not just data, for customers who cannot afford to slow down to stay safe.</p><p><strong>AI Tools Disclosure:</strong> As part of Cyberhaven's hiring process, we use recruiting tools that include AI-powered features to help with tasks like scheduling, note-taking, workflow automation, and other recruiting activities ('AI Tools'). The AI Tools may process information you provide during the application and interview process. When AI-assisted interview note taking is used, candidates are notified in advance and have the option to opt out of the AI-assisted interview note taking.</p><p><em>Cyberhaven is committed to creating a diverse environment and is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.</em></p>

AL, AK, AZ, AR, CA, CO, CT, DE, FL, GA, HI, ID, IL, IN, IA, KS, KY, LA, ME, MD, MA, MI, MN, MS, MO, MT, NE, NV, NH, NJ, NM, NY, NC, ND, OH, OK, OR, PA, RI, SC, SD, TN, TX, UT, VT, VA, WA, DC, WV, WI, WY

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<h2>Company Overview</h2><p>Deepgram is the leading platform underpinning the emerging trillion-dollar Voice AI economy, providing real-time APIs for speech-to-text (STT), text-to-speech (TTS), and building production-grade voice agents at scale. More than 200,000 developers and 1,300+ organizations build voice offerings that are ‘Powered by Deepgram’, including Twilio, Cloudflare, Sierra, Decagon, Vapi, Daily, Cresta, Granola, and Jack in the Box. Deepgram’s voice-native foundation models are accessed through cloud APIs or as self-hosted and on-premises software, with unmatched accuracy, low latency, and cost efficiency. Backed by a recent Series C led by leading global investors and strategic partners, Deepgram has processed over 50,000 years of audio and transcribed more than 1 trillion words. There is no organization in the world that understands voice better than Deepgram.</p><h2>Company Operating Rhythm</h2><p>At Deepgram, we expect an AI-first mindset—AI use and comfort aren’t optional, they’re core to how we operate, innovate, and measure performance.</p><p>Every team member who works at Deepgram is expected to actively use and experiment with advanced AI tools, and even build your own into your everyday work. We measure how effectively AI is applied to deliver results, and consistent, creative use of the latest AI capabilities is key to success here. Candidates should be comfortable adopting new models and modes quickly, integrating AI into their workflows, and continuously pushing the boundaries of what these technologies can do.</p><p>Additionally, we move at the pace of AI. Change is rapid, and you can expect your day-to-day work to evolve just as quickly. This may not be the right role if you’re not excited to experiment, adapt, think on your feet, and learn constantly, or if you’re seeking something highly prescriptive with a traditional 9-to-5.</p><h2>The Opportunity</h2><p>Voice is the most natural modality for human interaction with machines. However, current sequence modeling paradigms based on jointly scaling model and data cannot deliver voice AI capable of universal human interaction. The challenges are rooted in fundamental data problems posed by audio: real-world audio data is scarce and enormously diverse, spanning a vast space of voices, speaking styles, and acoustic conditions. Even if billions of hours of audio were accessible, its inherent high dimensionality creates computational and storage costs that make training and deployment prohibitively expensive at world scale. We believe that entirely new paradigms for audio AI are needed to overcome these challenges and make voice interaction accessible to everyone.</p><h2>The Role</h2><p>Deepgram is currently looking for seasoned Data Scientists with demonstrated experience solving hard data problems while exploring research frontiers to join our Research Staff. Conversational audio presents incredibly rich scientific, engineering, and infrastructure challenges that are orders of magnitude harder than working with text. As a Member of the Research Staff, you will help us to build an industrial “data factory” that will be used to power the next generation of Voice AI systems - unlocking the creation of models that go beyond basic transcription and comprehension, capturing nuanced meanings in complex conversations, adapting robustly to diverse speech patterns, and generating empathic responses with human-like, contextualized speech. You will collaborate closely with our product, engineering, and data teams to build and deploy models in the most scalable voice API on the planet. We look forward to you bringing your expertise, sharing insights from your latest experiments, and collaborating with us to push the boundaries of AI and voice technology.</p><h2>The Challenge</h2><p>We are seeking Research Staff who:</p><ul><li><p>See 'unsolved' problems as opportunities to pioneer entirely new approaches</p></li><li><p>Can identify the one critical experiment that will validate or kill an idea in days, not months</p></li><li><p>Have the vision to scale successful proofs-of-concept 100x</p></li><li><p>Are obsessed with using AI to automate and amplify your own impact</p></li></ul><p>If you find yourself energized rather than daunted by these expectations—if you're already thinking about five ideas to try while reading this—you might be the researcher we need. This role demands obsession with the problems, creativity in approach, and relentless drive toward elegant, scalable solutions. The technical challenges are immense, but the potential impact is transformative.</p><h2>What You'll Do</h2><ul><li><p>Drive high performance data acquisition, preparation and synthesis pipelines to generate data for the next generation of speech and language AI foundation models</p></li><li><p>Develop advanced characterizations of complex conversational audio utilizing a diverse toolkit of signals processing techniques and deep learning models</p></li><li><p>Collaborate with DataOps and Engineering to create automated systems which scale the ability of human annotators to label high value data and provide critical feedback on model outputs</p></li><li><p>Build advanced benchmarking methodologies and curated datasets for evaluating conversational voice systems</p></li><li><p>Document and present results of data experiments and analysis for internal and external audiences</p></li></ul><h2>You’ll Love This Role If You</h2><ul><li><p>Are obsessed with making sense out of complex and/or messy data</p></li><li><p>Enjoy building from the ground up and love to create new systems from scratch</p></li><li><p>Are passionate about AI and interested in leveraging data to solve hard problems</p></li><li><p>Are motivated by the prospect of scaling yourself using automation and AI models</p></li></ul><h2>It's Important to Us That You Have</h2><ul><li><p>Experience building data processing pipelines from a blank page and owning the entire data stack including data acquisition, characterization, cleaning, serving and transformation</p></li><li><p>Experience and expertise applying statistical methods and deep learning models to understand complex data</p></li><li><p>Strong communication skills and the ability to translate complex concepts in simple terms, depending on the target audience</p></li><li><p>Strong software engineering skills with particular emphasis on developing clean, modular code in Python and working with Pytorch</p></li></ul><h2>Nice to Haves</h2><ul><li><p>Background in Physics, Mechanical Engineering or Language Processing</p></li><li><p>Experience building models</p></li><li><p>Speech and audio experience</p></li></ul><p><em><strong>Notice</strong>: We're aware of individuals impersonating Deepgram recruiters. All legitimate Deepgram recruiting communication comes from an @</em><a href='http://deepgram.com'><em>deepgram.com</em></a><em> email address. If you've received a message claiming to be Deepgram, please forward it to [email protected].</em></p>

AL, AK, AZ, AR, CA, CO, CT, DE, FL, GA, HI, ID, IL, IN, IA, KS, KY, LA, ME, MD, MA, MI, MN, MS, MO, MT, NE, NV, NH, NJ, NM, NY, NC, ND, OH, OK, OR, PA, RI, SC, SD, TN, TX, UT, VT, VA, WA, DC, WV, WI, WY

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