Senior Data Scientist

OVERVIEW

This Senior Data Scientist will drive causal and machine learning-based analyses to measure the impact of product features on user behavior, engagement, and business outcomes, translating results into clear, actionable recommendations. The role partners closely with product, analytics engineering, and fellow data scientists to build in-house causal inference tools, define KPIs, build production-ready analytical workflows, and deliver high-quality, governed visualizations. Success in this role requires strong statistical judgment, experience with product-driven ML, and a focus on delivering insights that are both trustworthy and immediately usable by cross-functional stakeholders

KEY RESPONSIBILITIES

Causal Inference

- Design, implement, and productionalize statistically rigorous causal analyses to quantify the impact of product features on user behaviors, engagement metrics, and downstream business outcomes

- Develop and maintain causal frameworks that link product interventions to behavioral change, engagement shifts, and business performance

- Select and apply appropriate experimental and observational methods, leveraging regression- and ML-based approaches where appropriate to control for confounding and heterogeneity

- Validate causal findings through robustness checks, sensitivity analyses, and clear articulation of assumptions and limitations

- Translate results into clear, actionable recommendations that inform product strategy, marketing decisions, and executive-level prioritization

- Develop analytical notebooks and workflows that are reproducible, scalable, and suitable for deployment in production environments

KPI Development

- Partner with product and cross-functional stakeholders to define feature-level engagement and efficacy KPIs aligned with business objectives

- Incorporate model-derived signals (e.g., predicted engagement, risk scores, uplift estimates) into KPI frameworks where appropriate to improve measuremen...