Job Responsibilities:
• Strategic Partnership: Embed with product, engineering, and design leaders as a decision partner—framing ambiguous business questions, pressure-testing roadmap assumptions, and shaping bets before they are committed.
• Metric Frameworks: Define goal metrics, guardrails, and supporting metric trees for your product area. Decompose top-line outcomes into measurable inputs that teams can move.
• Experimentation: Design, power, and analyze A/B and quasi-experiments. Go beyond average treatment effects to understand heterogeneity, long-term impact, novelty effects, and cross-surface interactions.
• Causal Inference: Apply causal methods (difference-in-differences, synthetic control, instrumental variables, propensity scoring, switchback designs) where randomization is not feasible.
• Decision Modeling: Build opportunity sizing, forecasting, and ROI models that scale how the organization makes trade-offs—pricing, growth, retention, and long-range investment decisions.
• Deep Dives: Lead root-cause investigations into user behavior, funnel performance, retention, and engagement. Translate messy signal into clear, defensible recommendations.
• Collaboration: Serve as trusted analytics partner to PMs, designers, and engineers—translate product questions into research designs, analyses, and deliverables.
• Communication: Present findings and recommendations to senior leadership with clarity, structure, and its uncertainty.
• Mentorship & Best Practices: Mentor junior data scientists and analysts. Define internal standards for experiment design, statistical rigor, and reproducible analysis.