Senior Data Analyst, Experimentation

Misfits Market is a mission-driven, high-growth startup dedicated to reducing food waste and making shopping for sustainable, high-quality groceries easier and more affordable. We deliver organic produce, high-quality meats and seafood, plant-based proteins, dairy, bakery, wine, and other grocery items to nearly every zip code in 48 states at up to 30 percent off traditional grocery store prices. In 2022, Misfits Market acquired sustainable e-grocer Imperfect Foods and now leverages its in-house transportation network to deliver directly to consumers with one of the most carbon-efficient grocery delivery models on the market. By tackling inefficiencies in the food system, our passionate and motivated team of problem solvers helps save an average of 500,000 pounds of food per week from waste or lesser outcomes, with an all-time savings of 190+ million pounds of food.

Prioritizing our Customers                             

Doing more with less

Thinking Differently         

Respecting one another                             

Moving deliberately and quickly                   

Taking initiative and delivering 

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

• 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

• Prior experience in e-commerce or lifecycle marketing