Data Scientist – Supply Chain Optimization & Forecasting

Key Responsibilities

• Develop and deploy time-series forecasting and ML models for demand planning and forecast accuracy.
• Build solutions for demand sensing, anomaly detection, and predictive analytics.
• Lead end-to-end MEIO model development across stores, distribution centers, hubs, and supply chain networks.
• Develop mathematical optimization models balancing service levels, safety stock, lead times, inventory, capacity, and cost.
• Apply linear programming, mixed-integer programming, scenario analysis, and uncertainty-aware optimization.
• Optimize solver performance using reformulation, decomposition, heuristics, and parameter tuning.
• Build SQL-based ETL processes and data pipelines for production-ready models.
• Monitor model performance, validate outputs, and drive adoption through stakeholder collaboration and training.

Required Technical Skills

• 6+ years of experience in data science, operations research, supply chain optimization, and forecasting.
• Direct ownership of MEIO or comparable inventory optimization solutions.
• Strong Python and advanced SQL skills.
• Experience with Gurobi or comparable commercial optimization solvers.
• Optimization frameworks such as gurobipy, Pyomo, or OR-Tools.
• Time-series and ML forecasting techniques: ARIMA, Prophet, XGBoost.
• Strong understanding of safety stock, service levels, replenishment policies, demand variability, and lead-time variability.
• Experience with stochastic/robust optimization, simulation, and scenario planning.
• Knowledge of supply chain planning, inventory management, and S&OP processes.
• Experience deploying, monitoring, validating, and maintaining production models.

Schedule

• 6+ Months
• Hybrid

How to apply

• Share your updated resume highlighting relevant domain experience and MEIO projects.

Location

• Philadelphia, PA