Lead A/B testing and experimentation: hypothesis → design → measurement → analysis → decisioning.
Build predictive models that forecast outcomes and optimize store/business performance.
Apply causal inference methods when randomized tests aren’t possible.
Ensure statistical rigor, data quality, peer review, and reproducible workflows.
Evaluate and monitor model performance & stability
Partner with stakeholders to operationalize learnings and scale proven improvements.
Contribute to agile ceremonies and continuous improvement of analytics practices.
Requirements
Four-year degree or equivalent experience
3+ year as a Data Analyst with strong academic performance in a quantitative field; or strong equivalent experience
Advanced SQL experience writing complex queries
Competent and experienced in leveraging Python and R for analytical workflows
Solid problem solving, analytical skills, data curiosity, data mining, Data creation and consolidation
Support conclusions with a clear, understandable story that leverages descriptive statistics, basic inferential statistics, and data visualizations
Willingness to ask questions about business objectives and the measurement needs for a project workstream, and be able to measure objectives & key results
Excellent communication skills with the ability to speak to both business and technical teams, and translate ideas between them
Knowledge of AB Testing methods, time series, Forecasting models including statistical analysis
Experience in analytics tools such as: SQL, Excel, Hive, Spark, Python, R, Power BI, and/or equivalent technologies
Tech Stack
Python
Spark
SQL
Benefits
comprehensive health benefits and programs including medical, vision, dental, life insurance and more