Data Scientist

* W2 only - Unable to utilize C2C resources
* Top Skills Details Data Science, SQL, Python Top Skills' Details Needs a combination of Data Science (model prediction) and Operation Research (optimization, how can we do better with what we have).Develop and deploy time-series forecasting and machine learning models to improve demand planning across products, regions, and business segments.

Key Deliverables:

Develop and maintain SQL-based ETL processes and data pipelines supporting optimization models, scenario analysis, and production deployment.

Partner with data engineering teams to ensure the quality, availability, and integrity of model inputs, including demand variability, lead times, network structure, service policies, and operational constraints.

Establish governance, monitoring, and documentation to ensure model outputs are accurate, explainable, auditable, and production-ready. Contact Supplier Description Contractor , Data Science and Ops Research Scientist
- Supply Chain Planning COEKey Responsibilities Forecasting
- Data ScienceDevelop and deploy time-series forecasting and machine learning models to improve demand planning across products, regions, and business segments.
Build ML solutions for demand sensing, anomaly detection, predictive analytics, and forecast improvement.
Perform feature engineering, model development, validation, and statistical analysis using large-scale supply chain data.
Design and implement end-to-end data science pipelines, from data preparation through deployment, monitoring, and continuous improvement.
Evaluate model performance using accuracy, bias, SMAPE, forecast attainment, and other relevant metrics.
Collaborate with multiple teams to product ionize and scale data science solutions.

Inventory Optimization - MEIO Model Development & OwnershipLead the end-to-end development and ownership of Multi-Echelon Inventory Optimization (MEIO) models across retail stores, distribution centers, hubs, and customer-facing nodes.
Translate business requirements, inventory policies, service objectives, and operational constraints into mathematical optimization models and scalable decision-support solutions.
Design and maintain model objectives, assumptions, constraints, and optimization logic to balance service, inventory, safety stock, leadtime variability, capacity and cost.
Own model lifecycle management, including design, development, validation, deployment, monitoring, and recalibration as business conditions evolve.
Partner with business stakeholders to align model outputs with planning strategies, inventory policies, and service objectives.

Optimization & Solver EngineeringDevelop mathematical optimization models using Gurobi or comparable commercial solvers.
Apply techniques including linear programming, mixed-integer programming, scenario analysis, and uncertainty-aware optimization.
Improve model performance through reformulation, decomposition, heuristics, and solver parameter tuning.
Establish practices for reproducible testing, scenario analysis, benchmarking, and validation to ensure optimization recommendations are practical and implementable.

Data, Operationalization & AdoptionDevelop and maintain SQL-based ETL processes and data pipelines supporting optimization models, scenario analysis, and production deployment.
Partner with data engineering teams to ensure the quality, availability, and integrity of model inputs, including demand variability, lead times, network structure, service policies, and operational constraints.
Establish governance, monitoring, and documentation to ensure model outputs are accurate, explainable, auditable, and production-ready.
Support algorithmic planning and predictive scenario analysis using supply chain planning systems and…