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Director Of Data Sciences – Network Planning And Design

Working at Target means helping all families discover the joy of everyday life. We bring that vision to life through our values and culture. Learn more about Target here.

Target's Supply Chain is a large-scale, highly interconnected network spanning inventory, fulfillment, transportation, stores and distribution. Designing how that network should evolve requires solving complex decisions under uncertainty—balancing guest experience, cost, capacity, speed, resilience and capital investment.

The Director of Data Sciences - Network Planning and Design leads the data science and operations research capabilities that power these decisions. In this role, you will lead a team of data scientists responsible for building the analytical models and decision-support systems that shape Target's long-term supply chain architecture and investment roadmap. Your team will develop and evolve a portfolio of optimization models, simulations, digital twins, forecasting and capacity models as well as scenario-planning tools used to evaluate billions of dollars in potential network and capability investments.

As a Director of Data Sciences – Network Planning and Design you will:

Leadership and Cross-Functional Partnerships (50%)

• Lead, develop, and inspire a high-performing team of data scientists and operations research practitioners
• Set the analytical vision and roadmap for Network Planning & Design, translating strategic business questions into quantitative decision frameworks
• Serve as a thought leader in advanced analytics and supply chain network design, connecting technical work to business strategy
• Partner across Supply Chain, Finance, Technology, Stores, and other teams to ensure analytical capabilities address Target's most important network decisions
• Influence VP+ leaders by clearly communicating recommendations, trade-offs, uncertainty, and business impact

Advanced Modeling & Decision Science (25%):

• Lead 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

Tech, Data, AI and Innovation (25%):

• 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

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

About You:

• PhD or MS in Operations Research, Industrial Engineering, Computer Science, Mathematics, Statistics, Physics or relevant industry experience
• 10 plus years of experience leading and developing teams of applied data scientists and operations research scientists in optimization, simulation and advanced analytics
• 5 plus years of experience in mathematical optimization, simulation, forecasting, machine learning, statistical modeling and network modeling/planning
• Extensive experience in supply chain, logistics, retail, transportation, manufacturing or other large-scale network environments strongly preferred
• Highly proficient in Python, Scala, Java, SQL or R programming
• Significant demonstrated expertise in optimization theory (deterministic/stochastic), dynamic programming, linear algebra, probability and statistics
• Experience in statistical inference and deploying machine learning models at scale
• Experience translating complex analytical work into strategic recommendations and influencing senior leaders within and across global teams
• Strong problem-framing and communication skills, with the ability to operate effectively across technical and executive audiences

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 MN 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.