Senior Data Analyst, Misfits Market

• 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

Desirable

• The Data Analytics team is a pivotal part of the organization, closely collaborating with major stakeholders across the company including Product, Finance, Operations, Growth Marketing, Merchandising, and Logistics
• Our primary goal is to craft insightful reporting on key metrics, empowering immediate and impactful actions. We are recognized as trusted advisors, having a significant voice in guiding the strategic direction of these departments
• As a team, we foster both specialization and generalization. Each team member serves as a point of contact for a specific department, ensuring tailored support and expertise. Simultaneously, we emphasize a broad understanding of all departments we work with
• This ensures a cohesive, supportive environment where knowledge is shared, and support and collaboration is common
• As a Senior Data Analyst, Experimentation at Misfits Market, you’ll serve as the company’s go-to expert on experimental design and causal inference, while remaining hands-on with stakeholder dashboarding needs
• You’ll help evolve our experimentation culture by designing and evaluating controlled experiments, developing models to improve and simplify dashboard development, and mentor analysts on designing experiments and interpreting results
• 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