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.

This role requires a combination of Data Science and Operations Research expertise. Candidates should be comfortable building machine learning models as well as optimization and linear programming solutions that support supply chain planning and inventory decisions.

Key Responsibilities

Forecasting & Data Science

• Develop and deploy time-series forecasting and machine learning models to improve demand planning performance.

• Build and enhance demand forecasting models and machine learning solutions.

• Develop inventory optimization, linear programming, and Operations Research models that improve planning decisions.

• Analyze inventory performance, demand variability, and forecasting accuracy to improve business outcomes.

• Translate business requirements into scalable analytical solutions.

• Perform feature engineering, model development, validation, and statistical analysis using large-scale supply chain datasets.

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.

• 5+ years of experience in data science, operations research, supply chain optimization, demand forecasting, or a related analytical discipline.

• Strong understanding of supply chain planning, inventory management, service levels, replenishment strategies, and S& OP processes.

• Experience developing linear programming, mixed-integer programming, and optimization models using Gurobi, Pyomo, gurobipy, or comparable optimization frameworks.

• Hands-on experience applying machine learning and predictive analytics to business problems.

• Advanced proficiency with Python, SQL, and Databricks.

• Advanced Excel skills, including pivot tables, data validation, and analysis of large datasets.

• Experience building ETL processes, data pipelines, and production-ready analytical solutions.

• Strong understanding of forecasting methodologies, including time-series and machine learning-based approaches.

Preferred Qualifications

• Experience working within consumer goods, retail, manufacturing, logistics, or distribution environments.

• Familiarity with commercial supply chain planning or inventory optimization platforms.

• Experience designing and owning MEIO or similar inventory optimization solutions.

• Experience developing scalable solutions in enterprise environments.

• Strong feature engineering and model governance practices.

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