Staff Data Scientist, Strategic Insights & Analytics

10x Genomics•Pleasanton, CA

19h•Remote

About The Position

The Strategic Insights & Analytics team at 10x Genomics operates at the intersection of data science and business strategy. This team builds the analytical representation of how the company operates and grows to support strategic decisions, serving as the ultimate product. The team approaches this work as an engineering discipline, grounding models in the scientific process, versioning them in code repositories, and delivering them as internal products that support consequential business decisions. They are a team of high-agency, cross-disciplinary individuals who pursue the highest-leverage opportunities to deliver insights and analytics across the business. They share an 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. The team takes 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 where the successful candidate 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.

Requirements

Bachelor’s or Master's degree in a quantitative discipline (Statistics, Engineering, Mathematics, Computer Science, Data Science) or an MBA with a technical focus.
8+ 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.
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.
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 legacy tools like Tableau or Power BI.
Deep experience with sales processes and tools, specifically Salesforce CRM, quota and territory assignment, and the B2B enterprise demand generation funnel.
Understanding of how a business makes money and ability to trace a commercial decision through to revenue, margin, and cash.
Extreme bias for action and comfort working in a fast-paced environment with ambiguous requirements.
Assume AI can do something until proven otherwise, scope problems and verify your own work, and design for the end user.
Outstanding communication and interpersonal skills, with the ability to present technical work to senior management, sales leadership, and non-technical audiences and to influence cross-functional teams.

Responsibilities

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 the EDW and semantic layer (dbt, GitHub, Snowflake).
Modeling where growth comes from (new versus existing customers, by segment), activation, retention, expansion, cohort analysis, funnel conversion, and sales/marketing/service capacity and effectiveness.
Building territory, account, and instrument-level demand forecasts and LTV models.
Migrating planning models from spreadsheets to versioned models in GitHub.
Unifying the business review cadence on standardized views tied to company goals.
Enabling self-serve analytics and insights.
Replacing manual work with agentic workflows.
Program managing cross-functional initiatives.
Translating ambiguous business needs from leaders into structured analytical products.
Communicating recommendations clearly.