Data Scientist, Strategic Insights & Analytics

About 10x Genomics At 10x Genomics, accelerating our understanding of biology is more than a mission for us. It is a commitment. This is the century of biology, and the breakthroughs we make now have the potential to change the world. We enable scientists to advance their research, allowing them to address scientific questions they did not even know they could ask. Our tools have enabled fundamental discoveries across biology including cancer, immunology, and neuroscience. About the team and role The Strategic Insights & Analytics team sits at the intersection of data science and business strategy. We build the analytical representation of how the company operates and grows to support strategic decisions, our ultimate product. We treat this as an engineering discipline: grounding models in the scientific process, versioning in code repositories, and delivering as internal products that support consequential business decisions. We are a team of high-agency, cross-disciplinary individuals who pursue the highest-leverage opportunities to deliver insights and analytics, wherever they sit in the business. We share ambition and conviction that one person can now deliver what used to take a team, and that historically fragmented, static, spreadsheet-driven models can now converge into a single unified analytical model of the company. We take pride in fully leveraging modern AI tools to build analytical products and inform strategic decisions end-to-end. This is a high-impact individual contributor role. You will collaborate closely with senior business leaders and embed within teams across the organization to drive impact, then move on to the next highest-leverage problem. What you will be working on Data and semantic foundations: defining and implementing customer and market segments across systems, enriching with telemetry and other data; developing versioned metric definitions and business context so people and AI reason over a shared model; improving our EDW and semantic layer (dbt, GitHub, Snowflake) Customer, market, and growth models: modeling where growth comes from (new versus existing customers, by segment); activation, retention, expansion; cohort analysis; funnel conversion; sales/marketing/service capacity and effectiveness models Forecasting and planning models: building territory, account, and instrument-level demand forecasts and LTV models; migrating planning models from spreadsheets to versioned models in GitHub Enablement and automation: unifying the business review cadence on standardized views tied to company goals; enabling self-serve analytics and insights; replacing manual work with agentic workflows Stakeholder partnership: program managing cross-functional initiatives, translating ambiguous business needs from leaders into structured analytical products; communicating recommendations clearly To be successful you will need Education & experience: Bachelor’s or Master's degree in a quantitative discipline (Statistics, Engineering, Mathematics, Computer Science, Data Science) or an MBA with a technical focus; 5+ years experience in data science, analytics, corporate strategy, business operations, management consulting, or similar roles using analytics and applied data science to solve complex business problems and drive strategic decisions Analytical rigor: Hands-on depth in cohort and retention analysis, regression, time series, causal inference and experiment design, and supervised and unsupervised models; experience deploying machine learning models into production to solve commercial or operational problems Technical proficiency: SQL and Python for data manipulation and predictive modeling; reflexively AI-first, with experience shipping working systems using AI coding tools (Claude Code or similar) and the aptitude to learn new tools quickly; supporting stack: Git, GitHub, Snowflake, dbt or similar, CI/CD tools, comfortable building code-based, version-controlled reporting and dashboards that replace