Data Scientist (Big Data) III (Contractor)

Description
Data Scientist III (Supply Chain Optimization & Forecasting)
Long Term Contract
Hybrid Philadelphia, PA
Pay: Available on W2
Overview
We are seeking an experienced Data Scientist III to support a Supply Chain Planning Center of Excellence focused on forecasting, inventory optimization, and advanced analytics. This individual will design and deploy data science and operations research solutions that improve demand planning, inventory performance, and supply chain decision-making across complex business networks.
The ideal candidate brings a strong blend of data science, mathematical optimization, forecasting, and supply chain expertise, with experience developing and operationalizing scalable models that drive measurable business outcomes.
Key Responsibilities
Forecasting & Data Science

• Develop and deploy time-series forecasting and machine learning models to improve demand planning performance.
• Build 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 datasets.
• Design and implement end-to-end data science pipelines, including data preparation, deployment, monitoring, and continuous improvement.
• Evaluate model performance using forecasting and business metrics such as forecast accuracy, bias, attainment, and error measurements.
• Partner with cross-functional teams to scale and productionize advanced analytics solutions.

Inventory Optimization & MEIO

• Lead the development, enhancement, and ownership of Multi-Echelon Inventory Optimization (MEIO) models.
• Translate business requirements, operational constraints, and planning policies into mathematical optimization models and decision-support tools.
• Develop optimization logic that balances inventory investment, service levels, safety stock, lead-time variability, network constraints, and cost objectives.

Optimization Engineering

• Build and maintain mathematical optimization models using commercial optimization solvers such as Gurobi or similar platforms.
• Apply optimization techniques including linear programming, mixed-integer programming, scenario modeling, simulation, and uncertainty-aware optimization.

Data Engineering & Operationalization

• Develop and maintain SQL-based ETL processes and data pipelines that support optimization and forecasting solutions.
• Partner with data engineering teams to ensure data quality, availability, and reliability.
• Create monitoring, governance, and documentation processes to support production-ready solutions.

Requirements
Required Qualifications

• Bachelor's degree in Data Science, Operations Research, Industrial Engineering, Statistics, Applied Mathematics, Computer Science, Supply Chain, or a related field; advanced degree preferred.
• 6+ years of experience in data science, operations research, supply chain optimization, demand forecasting, or a related analytical discipline.
• Experience designing and owning MEIO or similar inventory optimization solutions.
• Strong understanding of supply chain planning, inventory management, service levels, replenishment strategies, and S& OP processes.
• Experience developing optimization models using Gurobi, Pyomo, gurobipy, or similar optimization frameworks.
• Hands-on experience applying machine learning and predictive analytics to business problems.
• Advanced proficiency with Python and SQL.
• Experience building ETL processes, data pipelines, and production-ready analytical solutions.
• Strong understanding of forecasting methodologies, including time-series and machine learning-based approaches.
• Experience with scenario analysis, simulation, stochastic optimization, or robust optimization techniques.

Preferred Qualifications

• Experience working within consumer goods, retail, manufacturing, logistics, or distribution environments.
• Familiarity with commercial supply chain planning or inventory optimization platforms.
• Experience developing scalable solutions in enterprise environments.
• Strong software engineering and model governance practices.

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