Staff Data Scientist, Strategic Insights & Analytics

10x Genomics•Pleasanton, CA

5h•$198,500 - $268,500

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 functions and expands to inform strategic decisions. They approach this as an engineering discipline, grounding models in scientific processes, managing versions in code repositories, and delivering them as internal products to support critical business choices. The team comprises high-agency, cross-disciplinary individuals focused on high-leverage opportunities to deliver insights and analytics across the business. They are driven by the belief that a single individual can achieve what previously required a team and that fragmented, static, spreadsheet-based models can be unified into a single analytical model of the company. They leverage modern AI tools to build analytical products and inform strategic decisions comprehensively. This is a high-impact individual contributor role where the successful candidate will collaborate closely with senior business leaders and embed within various organizational teams to drive impact, then move on to the next high-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 of 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.
Proficiency in SQL and Python for data manipulation and predictive modeling.
Reflexively AI-first approach with experience shipping working systems using AI coding tools (Claude Code or similar) and the aptitude to learn new tools quickly.
Experience with 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 the 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.
Ability to assume AI can do something until proven otherwise, scope problems, verify 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 to ensure shared understanding for both people and AI.
Improving the EDW and semantic layer using tools like dbt, GitHub, and Snowflake.
Modeling growth drivers, including new vs. existing customers, by segment, and analyzing activation, retention, expansion, cohort performance, 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 with 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.