Data Scientist/Operations Research

Title: Data Scientist/Operations Research

Location: 100% REMOTE

Duration: 6+ Months, Multi-year Contract.

Job Description:

We are seeking a Data Scientist/Operations Researcher to design and implement advanced discrete event simulations and develop digital twin capabilities for our supply chain. In this role, you will collaborate with cross-functional teams—including engineering, operations, product management, and other data scientists—to model complex supply chain scenarios, run “what-if” analyses, and translate insights into actionable strategies. While simulation is the primary focus of this position, you will also leverage optimization and operations research methods to enhance our decision-making processes.

Key Responsibilities:

• Simulation Model Development
• Design, develop, and maintain discrete event simulation models to evaluate and improve supply chain operations.
• Build scalable simulation frameworks in Python (e.g., using SimPy or other simulation libraries), with openness to exploring other platforms or tools.
• Collaborate with stakeholders to define key performance indicators (KPIs), data requirements, and realistic assumptions in simulation modeling.
• Digital Twin Architecture
• Lead the development of a digital twin for Sam’s Supply Chain, integrating real-time data feeds and advanced analytics.
• Ensure the digital twin can replicate physical processes accurately and provide actionable insights for operational improvements.
• Optimization & Operations Research
• Apply advanced optimization methods (linear programming, mixed-integer programming, heuristic algorithms, etc.) to support supply chain decision-making.
• Work closely with cross-functional teams to identify areas of opportunity for optimization in transportation, inventory, and warehouse operations.

Qualifications

Education & Experience:

• Master’s or Ph.D. in Operations Research, Industrial Engineering, Computer Science, Data Science, or a related field.
• 3+ years of hands-on experience in building discrete event simulation models and running complex simulation projects.
• Demonstrated experience with optimization techniques in a supply chain or related domain.

Technical Skills:

• Programming Languages: Proficiency in Python is required; experience with simulation libraries (e.g., SimPy, AnyLogic, Arena, or similar) is highly preferred.
• Optimization & OR: Knowledge of linear programming, mixed-integer programming, and heuristic algorithms; familiarity with OR tools (e.g., PuLP, Pyomo, Gurobi, CPLEX) is advantageous.
• Data Handling: Strong skills in SQL, data wrangling, and data visualization (e.g., Tableau, Power BI, matplotlib, Plotly).
• Cloud & Big Data: Familiarity with cloud platforms (e.g., Azure, AWS) and big data technologies (e.g., Spark, Hadoop) is a plus.
• Simulation Best Practices: Experience with model calibration, validation techniques, and scenario-based analysis.