Senior Data Scientist, Experimentation

As a Senior Data Scientist on the experimentation team, you guide how product and engineering teams design and interpret experiments to move quickly without sacrificing rigor. You own the measurement strategy for your domain and help teams understand not just if a change works, but why and when it generalizes. You tackle non-standard experiments with low traffic, shared supply, or long-horizon outcomes, shaping decisions that impact platform health and growth. This role blends methodological leadership with practical tooling, enabling cross-functional partners to run robust, scalable experiments.

• Own the experimentation and measurement strategy for your domain, from framing questions to decision review
• Provide guidance, tooling, and protocols to accelerate experimentation with rigor
• Design experiments beyond standard A/B tests for low-traffic surfaces, shared supply, or long-horizon outcomes
• Investigate why results occur and their generalizability across users, markets, and time
• Assess impact of product decisions on platform health and growth, flagging risks
• Define and operationalise metric frameworks with guardrails for long-observable outcomes
• Improve measurement sensitivity via metric design, variance reduction, and exposure definition
• Standardise experimentation processes using automation and AI when beneficial
• Influence roadmap with evidence, and advocate against work lacking evidence
• Review designs and analyses; mentor less experienced data scientists

• Extensive experience in data science or a related quantitative role with product impact
• Authoritative command of experimentation and causal inference, Bayesian methods, and variance reduction
• Proficiency in Python and SQL; strong statistical modelling and ML techniques
• Ability to define and operationalise product and feature-level metrics
• Ability to enable and improve cross-functional collaboration without direct authority
• Critical thinking to validate results and assess long-term implications
• Excellent communication to explain measurement and uncertainty to varied audiences
• Bachelor's degree in a quantitative field

• Cross-functional collaboration
• Strong communication
• Critical thinking
• Python
• SQL
• Statistical modelling