Sr. Data Scientist - Network Modeling & Optimization

Best Buy is hiring a senior data science contributor to lead network modeling and optimization work that supports supply chain planning and one-off decision needs. This hybrid role in Minneapolis, MN combines hands-on model development with scenario evaluation, validation, and clear stakeholder communication.

The Sr. Data Scientist focuses on updating, running, and improving existing supply chain network models, and also contributes to readiness for production while helping develop new modeling approaches when required.

What you’ll do

• Develop and maintain analytical inputs and optimization models covering facilities, transportation lanes, demand, product flows, costs, capacities, service requirements, and business rules.
• Assess strategic and tactical scenarios across facility location, network assignments, capacity, sourcing, inventory placement, transportation, and product flow.
• Validate model behavior, diagnose infeasibilities and data-quality issues, and communicate assumptions, limitations, tradeoffs, and recommendations to business and technical stakeholders.
• Turn ambiguous supply chain questions into structured analytical problems by defining objectives, decisions, constraints, assumptions, data requirements, and expected outputs.
• Translate complex physical processes into simplified functions that preserve key real-world characteristics while remaining usable as model inputs.
• Support end-to-end network modeling and optimization efforts from business-problem definition through model development, validation, interpretation, and recommendation.
• Provide technical guidance and mentorship to Data Scientists and analysts, establishing reusable modeling practices, documentation standards, and quality controls.

Qualifications

• Bachelor’s degree in a quantitative field (Operations Research, Industrial Engineering, Mathematics, Statistics, Computer Science, Economics, Engineering, Supply Chain Analytics, or related) or equivalent experience.
• 4+ years of relevant experience in data science, operations research, optimization, supply chain analytics, forecasting, simulation, or a related analytical field.
• 4+ years of leading complex analytical projects and translating ambiguous business questions into structured modeling approaches.
• 4+ years hands-on experience with data analytics tools (e.g., SQL, Python, R) and machine learning and/or optimization tools (Python, R, Gurobi, Vertex AI).
• Strong knowledge of optimization, operations research, statistical modeling, forecasting, simulation, machine learning, or another advanced analytical discipline.
• Ability to explain technical concepts, model results, and business recommendations clearly to both technical and non-technical audiences.

Tools and technologies

• SQL, Python, R, Gurobi, Vertex AI, AIMMS

Preferred qualifications

• Advanced degree in a quantitative field (Operations Research, Industrial Engineering, Mathematics, Statistics, Computer Science, Supply Chain Analytics, or related).
• Experience with supply chain network design, transportation, distribution, fulfillment, inventory, logistics, or capacity planning.
• Experience developing optimization models using linear programming, mixed-integer programming, network flow, facility location, or assignment modeling.
• Experience defining model inputs, decision variables, constraints, objective functions, scenarios, and outputs, including diagnosing model infeasibilities.
• Familiarity with AIMMS or comparable optimization platforms, libraries, or solvers (direct AIMMS experience is preferred but not required).
• Experience providing technical leadership, mentoring Data Scientists or analysts, and communicating recommendations to business leaders.

Compensation and logistics

• Location: Minneapolis, MN (hybrid)
• Salary: USD 106,200 - 190,300 per year
• Position type: Full time
• Application deadline: Minimum of 5 days from the posting date

Benefits

• Competitive pay
• Great employee discount
• Financial savings and retirement resources
• Support for physical and mental well-being
• Paid time off (vacation or PTO) for full-time and part-time employees based on work location, employment status, salary or hourly status (exempt/non-exempt), and years of continued or bridged service
• Leaves of absence (LOA) and potential pay sources based on eligibility (length depends on situation, where you live, full-time/part-time status, and federal and state regulations)
• Intermittent or reduced-schedule leave for certain medical or family care leaves
• Certain roles may be eligible for incentive pay to drive performance and offer recognition