Manager - Pricing Data Science

The Manager - Data Science and Analytics plays a critical role in revenue and margin management for the Merchandising organization by performing various pricing analyses to exceed the financial targets. This highly visible individual will manage the daily and weekly promotions for print and digital marketing vehicles, so to be successful, strong analytical skills and business savviness is vital. This Team Member will develop and use analytics tools to draw insights and provides actionable recommendations while exhibiting higher-order critical thinking under ambiguous situations.

Major Activities

• Machine Learning Forecasting: Maintain, regularly run, and potentially adjust time-series forecasting pipelines with backtesting, accuracy diagnostics, drift detection, and ongoing monitoring.
• Pricing optimization: Maintain, regularly run and potentially adjust pricing/markdown optimization engines (e.g., Gurobi, CP-SAT), including feasibility checks, constraint adjustments, relaxations, and scenario analysis.
• Mathematical modeling: Translate new business rules (e.g., new constraints for pricing) into robust mathematical formulations.
• Production engineering: Maintain a modular codebase across forecasting, optimization, and data workflows; keep ensure code quality, test coverage, and documentation. Maintain overrides to handle data quality issues.
• Reporting & impact measurement: Own reporting for the pricing engine, turn recommendations into stakeholder-ready insights and quantify business impact.
• Cross-functional collaboration: Partner with Merchants and Pricing Advisory to translate business needs into features for retail pricing algorithm
• Develop and implement user-friendly analytics dashboards and tools that perform complex analysis manipulating large data sets to identify actionable business insights
• Initiate, partner with internal teams on process improvement initiatives
• Ad-hoc projects as identified by the supervisor

Other duties as assigned

Preferred Education/Experience

• Bachelor’s Degree or equivalent experience required.
• Advanced MS Excel required.
• Proficiency in forecasting and machine learning: Ability to build and deploy time-series forecasting models including feature engineering and robust backtesting & monitoring.
• Data manipulation and analysis: Strong ability to work with large datasets using Python (pandas/NumPy) and SQL, performing clean feature creation and diagnostic analysis.
• Data Engineering: Previous experience building DBT ETLs on cloud-based warehouses like BigQuery and working in Vertex AI.
• Problem-solving ability: Strong analytical skills to decompose complex business problems, balance solution quality vs runtime, and implement pragmatic fallbacks.
• Master’s degree in economics, data analytics, or math related field preferred

Minimum Type of Experience Required

• 7+ years of relevant work experience

Other

• SQL and Python required, Tableau or Power BI is preferred

Applicants in the U.S. must satisfy federal, state, and local legal requirements of the job.