Senior Data Analyst, Experimentation

Responsibilities

• Own experimentation analytics.
• Design, monitor and interpret A/B and multivariate tests across Product and Marketing.
• Partner with Product Managers and Marketing leads to prioritize experiments using frameworks like ICE or PIE.
• Translate experimental results into business recommendations.
• Collaborate with engineering to ensure consistent event tracking and instrumentation design.
• Develop internal experimentation frameworks.
• Build dbt models and dashboards that automate experiment tracking, power statistical analyses, and improve interpretability.
• Mentor analysts: guide the team in best practices for causal inference, power analysis, metric selection, and communicating uncertainty.
• Improve data infrastructure: maintain and improve dbt models, metrics definitions, and self-serve data assets.
• Develop descriptive reporting dashboards across Product, Merchandising, and other teams.
• Dive into complex SQL and break down problems.
• Identify areas of opportunity to move from descriptive to predictive analytics, and ad-hoc to self-serve reporting.
• Maintain analytics roadmap to prioritize initiatives, communicate timelines, and ensure successful, timely completion of deliverables.

Qualifications

• Master’s degree in Data Science, Computer Science, Statistics, or a related field with 3+ years of relevant experience, or Bachelor’s degree in the same fields with 5+ years of relevant experience.
• Expert-level SQL skills - you are comfortable writing complex queries and optimizing for performance.
• Deep understanding of experiment design, causal inference, and statistical testing.
• Experience with dbt and data modeling best practices.
• Proficiency with Python or R for statistical analysis.
• Experience with visualization tools, such as Mode, Tableau, PowerBI, etc.
• Experience with data pipelines - have created and/or are comfortable communicating ETL needs to engineering.
• Strong communication skills - you can gather user stories and translate data insights to stakeholders of varying levels of technical knowledge.
• Experience working as part of a cross-functional data team.