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 on the Supply Chain Network Optimization (SCNO) team, which is part of Global Supply Chain and Logistics. The team focuses on defining and enabling an efficient, reliable, and best-in-class supply chain using advanced mathematical techniques like ML, AI, OR, MILP, and DES. The scientist will study complex supply chain problems, develop cutting-edge solutions, analyze large datasets, and build algorithms, simulation, and optimization models. The role involves optimizing Target's Global Supply Chain end-to-end, from sourcing to delivery, to enhance guest experience and drive profitable growth. The position requires a strong understanding of supply chain operations, programming skills in 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

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.