Sr Applied Data Scientist - Supply Chain Optimization

Target • Brooklyn Park, MN

5d • $98,000 - $211,000 • Hybrid

About The Position

The Sr Applied Data Scientist – Supply Chain Optimization role is part of Target Data Sciences’ Global Supply Chain and Logistics team. The team uses operations research, simulation, and machine learning to support end-to-end supply chain decisions. The role develops and manages predictive and prescriptive algorithms that automate and optimize decisions at scale, including writing high-performance, scalable Python and designing analytical solutions that generate insights and recommend actions.

The position involves reviewing and iterating on optimization and machine-learning algorithms with other data scientists, developing mathematical models, and working with engineers to deploy algorithms in production at scale. Models may run many times each day across millions of combinations of stock keeping units and distribution networks. The role also partners with business stakeholders to understand retail processes and balances model granularity and features with performance, reliability, and usability. The position contributes to engineering standards, tools, and processes.

The role is a Hybrid/Flex for Your Day arrangement. Work is performed both onsite at the assigned Target HQ Sunnyvale location and virtually, depending on the role, team, and daily tasks. Work duties cannot be performed outside the country of the primary work location unless otherwise prescribed by Target.

Requirements

• PhD or MS in Industrial Engineering, Operations Research, Computer Science, Applied Mathematics, Statistics, Physics, or a related quantitative field.
• At least 3 years of experience leading large-scale implementations of optimization, simulation, machine learning, and deep learning.
• Extensive experience writing high-performance Python code and deploying algorithms in production.
• Proficiency in predictive and prescriptive algorithms.
• Expertise formulating and implementing mathematical models, including mixed-integer programming, stochastic dynamic programming, and reinforcement learning.
• Experience implementing advanced statistical techniques such as regression, clustering, PCA, and time-series forecasting.
• Proficiency in application/software architecture, including definition and process modeling.
• Experience writing production datasets in SQL/Hive or building internal or production data tools for research or experimentation in a scripting language such as Python.
• Ability to produce reasonable documents and narratives that suggest actionable insights.
• Excellent communication skills and ability to present data-driven stories through appropriate visualizations, graphs, and narratives.
• Strong knowledge of supply chain optimization, including inventory, transportation, sourcing, distribution, fulfillment, and planning.
• Strong computer science fundamentals, including data structures, design, algorithms, programming, and information retrieval.
• Ability to write efficient, well-structured, understandable, testable, and maintainable code.
• Ability to communicate technical solutions effectively to business, product, and engineering partners.
• Ability to manage ambiguity, prioritize progress over perfection, and prioritize business impact and end-user needs.
• Attention to detail, curiosity about supply chain problems, and ability to use data to answer open questions.
• Self-driven, results-oriented approach with strong ownership, sound judgment, and ability to move quickly while maintaining high technical standards.
• Collaborative approach, commitment to continuous learning and knowledge sharing, and interest in building reliable AI systems that create business value.

Responsibilities

• Review and iterate on optimization and machine-learning algorithms with fellow data scientists, and develop mathematical models.
• Collaborate with engineers to design and deploy algorithms in production at scale.
• Work with business partners to understand the retail business and its processes.
• Resolve tradeoffs among model granularity, features, performance, reliability, and codebase usability.
• Improve engineering standards, tooling, and processes.
• Develop understandable, testable, maintainable code and analytical solutions that produce actionable insights.

Benefits

• Eligible team members and dependents may receive comprehensive health benefits and programs, which may include medical, vision, dental, and life insurance.
• 401(k)
• Employee discount
• Short-term disability
• Long-term disability
• Paid sick leave
• Paid national holidays
• Paid vacation

What This Job Offers

• Job Type: Full-time
• Career Level: Senior