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

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