Lead Data Scientist - Network Planning and Design (applied ML, optimization, simulation)

• Define and structure ambiguous supply chain problems into clear frameworks for decision-making in partnership with Network Design, Flow, and Capacity Planning teams
• Synthesize insights into compelling narratives for executive audiences and guide decision-making at scale
• Influence senior stakeholders across Supply Chain, Operations, Finance, Technology, Strategy and Merchandising

• Own the development of optimization, simulation, forecasting, digital twin, and machine learning capabilities supporting Target's long-term network strategy
• Apply operations research and advanced analytics to decisions including network footprint, capacity planning, inventory placement, product flow, automation, transportation, and reverse logistics
• Ensure models accurately represent real-world constraints, uncertainty, and operating dynamics while remaining scalable and actionable
• Establish strong practices for scenario analysis, sensitivity testing, model validation, and decision support
• Build reusable analytical capabilities that enable faster and more consistent strategic decision-making
• Own, maintain, and continuously enhance strategic planning models to ensure accuracy, scalability, and alignment with evolving business needs

• Partner across Supply Chain, Operations, Finance, Technology, Strategy, and Merchandising teams to maintain a strong pulse on customer needs, priorities, and decision contexts, aligning cross-functionally on assumptions, decisions, and business requirements
• Drive clarity across cross-functional teams regarding constraints, assumptions, and strategic implications

• Partner with Engineering, Product, and Technology teams to transform analytical models into scalable decision-support tools and products
• Advance the use of modern optimization solvers, cloud computing, machine learning, and AI where they improve model performance or decision quality
• Establish strong practices for model governance, reproducibility, testing, documentation, and auditability
• Champion experimentation and emerging methods that advance Target's network planning capabilities
• Mentor and coach data scientists and analysts in structured problem solving, systems thinking, and executive communication
• Elevate modeling and analytical standards within the team

Core responsibilities of this job are described within this job description. Job duties may change at any time due to business needs.

• PhD/MS in Operations Research, Industrial Engineering, Computer Science, Mathematics, Statistics, Physics or related quantitative field
• 5+ years of experience leading large-scale implementations of supply chain optimization, simulation and machine learning modeling end to end
• Demonstrated proficiency in one or more programming languages: Python, R, Kotlin or Java
• Demonstrated experience writing highly performant code and deploying algorithms in a production environment. Proficient in predictive/prescriptive algorithms and ML Ops
• Experience working with large event-driven distributed systems and multi-threaded applications
• Experience in application/software architecture (definition, process modeling, etc.)
• Experience writing production datasets in SQL/Hive or building internal/production data tools for research or experimentation in a scripting language like Python
• Experience working with mathematical optimization libraries or solvers (e.g. Gurobi)
• Passion for solving relevant real-world problems using a data science approach
• Experience in implementing advanced statistical techniques like regression, clustering, PCA, forecasting (time series), etc.
• Experience producing reasonable documents/narratives suggesting actionable insights
• Excellent communication skills with an ability to clearly tell data driven stories through appropriate visualizations, graphs, and narratives
• Self-driven and results oriented; able to meet tight timelines
• Collaborative team player with ability to partner effectively across time zones

This position will operate as a Hybrid/Flex for Your Day work arrangement based on Target's needs. A Hybrid/Flex for Your Day work arrangement means the team member's core role will need to be performed both onsite at the Target HQ location the role is assigned to and virtually, depending upon what your role, team and tasks require for that day. Work duties cannot be performed outside of the country of the primary work location, unless otherwise prescribed by Target.