Senior Data Scientist, Product Analytics

ABOUT THE ROLE We’re looking for a Senior Data Scientist, Product Analytics to lead analytics for Handshake’s Recruiting marketplace. You’ll drive measurement and strategy across marketplace health, liquidity, pricing, and product-led growth, partnering closely with Product, Engineering, and Leadership to shape the future of our marketplace. This is a highly impactful, hands-on role where you’ll own analytics strategy, influence product direction, and work alongside our Relevance (ML) team to ensure our models deliver measurable business impact. WHAT YOU’LL DO - Partner with Product, Engineering, and R&D leadership to define and measure marketplace health, liquidity, pricing, and growth. - Own analytics strategy, domain metrics, goal setting, and reporting for your product area. - Lead experimentation, including test design, instrumentation, analysis, and recommendations. - Partner with our Relevance team to evaluate and benchmark machine learning models. - Conduct deep analyses across user behavior, funnels, cohorts, and marketplace performance to uncover actionable insights. - Collaborate with Analytics Engineering to define trusted metrics and scalable data models. - Build dashboards and reporting that enable fast, data-driven decision making. - Champion AI-powered workflows and help shape the future of Product Analytics at Handshake. DESIRED CAPABILITIES - 5+ years of experience as a Data Scientist or Product Analyst driving product strategy through data. - Expert-level SQL skills with experience analyzing large, complex datasets. - Strong experience with experimentation, A/B testing, and statistical analysis. - Experience partnering closely with Product Managers, Engineers, and cross-functional stakeholders. - Python experience for analytics (e.g., Jupyter notebooks, pandas). - Strong business intuition with the ability to translate data into strategic recommendations. - Excellent communication skills and the ability to influence technical and executive audienc

Department: Engineering; Team: Data & Machine Learning