Retail Pricing Data Scientist
We’re looking for a data scientist with deep expertise in retail pricing to build models and tools that directly shape pricing strategy across regular, promotional, and markdown scenarios. You’ll help drive key decisions around elasticity, promotions, and revenue optimization—working closely with Pricing, Merchandising, and Finance teams to deliver measurable impact.
What You’ll Do
- Develop and deploy models for price optimization, markdown forecasting, and promotional lift
- Design and analyze pricing experiments (A/B tests, geo-lift, causal studies)
- Use Python and SQL to build production-ready solutions and automate pricing workflows
- Apply techniques like regression, time series (ARIMA, Prophet), XGBoost, and LightGBM
- Translate insights into clear, strategic recommendations that drive margin and sell-through
- Build intuitive dashboards and visualizations in Tableau, Power BI, or matplotlib
- Partner with business teams to define KPIs, monitor impact, and evolve pricing strategy
What You’ll Bring
- 4–6+ years applying data science to pricing strategy in a retail or consumer-facing environment
- Expert-level skills in Python (pandas, scikit-learn, PyMC, etc.) and SQL
- Experience designing and evaluating pricing experiments and demand estimation models
- Hands-on knowledge of elasticity modeling, promotions, and competitive pricing
- Strong communication skills and ability to align data with business outcomes
- Degree in Data Science, Statistics, Computer Science, or related field
Additional Requirements
- Bachelor’s or Master’s degree in a quantitative discipline such as Statistics, Data Science, Mathematics, Computer Science, Economics, Engineering, or a related field
- Must be authorized to work in the United States without current or future sponsorship
- Must be available to work onsite in Orlando, FL a minimum of four (4) days per week as part of a hybrid schedule
