Description
We are seeking a Lead Data Scientist – Network Planning and Design to join our Target Data Sciences - Supply Chain Optimization team. As a Lead Data Scientist, you will be responsible for building analytical models and decision-support systems that shape Target's long-term supply chain architecture and investment roadmap.
The pay range for this position is $132,000.00 - $286,000.00, and Target offers comprehensive health benefits, 401(k), employee discount, short-term disability, long-term disability, paid sick leave, paid national holidays, and paid vacation.
Responsibilities:
- Define and structure ambiguous supply chain problems into clear frameworks for decision-making
- 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
- Partner across Supply Chain, Operations, Finance, Technology, Strategy, and Merchandising teams to maintain a strong pulse on customer needs, priorities, and decision contexts
- 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
- Mentor and coach data scientists and analysts in structured problem-solving, systems thinking, and executive communication
Requirements:
- 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
- Experience working with large event-driven distributed systems and multi-threaded applications
- Experience in application/software architecture
- 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
- Passion for solving relevant real-world problems using a data science approach
- Excellent communication skills with an ability to clearly tell data-driven stories