Sr Operations Research Scientist - Supply Chain Network Optimization (Python, ML, Simulation)

Target • Minneapolis, MN

6d • Hybrid

About The Position

This role is for a Sr Operations Research Scientist focused on Supply Chain Network Optimization. The individual will be responsible for shaping the future Supply Chain and Logistics strategy for a fortune 50 company, optimizing Target’s Global Supply Chain from sourcing to delivery. The role involves analyzing large datasets and developing complex algorithms, simulation, and optimization models to solve real-world problems. The Supply Chain Network Optimization (SCNO) team is a global team that defines and enables an efficient, reliable, and best-in-class supply chain using techniques like ML, AI, OR, MILP, and DES across the value chain (Purchasing, Transportation, Multi Echelon Inventory, Last-Mile, and Process Optimization). The scientist will study complex supply chain problems, understand the business, and develop cutting-edge solutions, requiring strong experience with large data sets, programming skills (Python/R), and foundational knowledge of probability theory, machine learning, and Monte Carlo simulations. Extensive knowledge of statistics, operations research, and discrete event simulation is ideal.

Requirements

• PhD or MS in Operations Research, Industrial Engineering, Computer Science, Data Science, Applied Mathematics, Physics or equivalent work experience
• 3+ years of industry experience in supply chain optimization, simulation and probability statistics or equivalent domain experience
• Demonstrated programming experience using Python or R as well as advanced SQL querying skillset
• Proven experience in data pipeline building in the Hadoop ecosystem (PySpark)
• Extensive knowledge of supply chain concepts such as forecasting, inventory planning, optimization and logistics
• Knowledge of statistics and data mining techniques/tools to analyze and derive insights from historical sales data and simulation or experiment results
• Deep passion for problem solving, empirical research and continuous improvement
• Excellent communication skill with the ability to clearly tell data driven stories through appropriate visualizations, graphs, and narratives
• Self-driven and results oriented - able to meet tight timelines
• Motivated, team player with ability to collaborate effectively across global team

Nice To Haves

• Foundational understanding of probability theory, machine learning and Monte Carlo simulations.
• Extensive knowledge of statistics, operations research and discrete event simulation is ideal.

Responsibilities

• Know your business and understand supply chain operational metrics and cost of end to end operations of supply chain.
• Analyze large amounts of supply chain data at the most granular level and develop key metrics to evaluate the performance and optimization opportunities for supply chain across sales, transportation, operations and inventory.
• Perform root cause analysis to understand key drivers related to operational performance and variance in the projected outcomes.
• Utilize operations research methodologies (linear programming, stochastic processes, simulation) to solve complex business problems.
• Collaborate with cross-functional teams including software engineers, applied data scientists and business stakeholders to gather inputs assumptions and understand business process along the way.
• Interpret results from the models and provide insights to the leadership team.
• Develop clear inferences with data to influence decision making with Sr leaders.

Benefits

• Comprehensive health benefits and programs (medical, vision, dental, life insurance)
• 401(k)
• Employee discount
• Short term disability
• Long term disability
• Paid sick leave
• Paid national holidays
• Paid vacation

What This Job Offers

• Job Type: Full-time
• Career Level: Senior