Sr Data Scientist - Global Supply Chain and Logistics

Pay range: $ - $. Pay is based on several factors including labor market, education, experience, and certifications.

Target invests in team members and their families with comprehensive health benefits and programs, including medical, vision, dental, life insurance, and more. Other benefits include 401(k), employee discount, short and long-term disability, paid sick leave, paid national holidays, and paid vacation. Discover further benefits at

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

A role with Target Data Sciences means the chance to help develop and manage state-of-the-art predictive and prescriptive algorithms that use data to automate and optimize decisions  Target Data Science – Global Supply Chain and Logistics team leverages operations research, simulation, and machine learning to help Target make intelligent, end‑to‑end supply chain decisions. This involves writing high‑performant, scalable code as well as designing analytical solutions to extract insights and prescribe best actions.

You’ll work in an environment that provides the freedom and agility of a startup, with the security and vast resources of a large established company.

• Work closely with fellow data scientists to review and iterate on optimization and machine learning algorithms and develop state‑of‑the‑art mathematical models.
• Collaborate with engineers to design and deploy algorithms in production  models run many times a day for millions of combinations of stock‑keeping units and distribution networks.
• Work with business partners to learn about the retail business and processes in play.
• Ideate and resolve trade‑offs between model granularity and features as well as performance, reliability, and usability of our codebase. Improve engineering standards, tooling, and processes.

• Strong knowledge of supply chain optimization – inventory, transportation, sourcing, distribution, fulfillment, planning, etc.
• Strong computer science fundamentals and a love for rock‑solid, well‑structured, and efficient code: data structures, algorithms, programming languages, and information retrieval.
• Strong technical and communication skills to deliver with quality and evangelize technical solutions to business, product and engineering partners.
• Ability to write understandable, testable code with an eye toward maintainability.
• You constantly think about the end‑user for solutions you develop, prioritizing business impact over technical sophistication.
• Ability to deal with ambiguity, and prioritize progress over perfection.
• You have an eye for detail and relentless curiosity for supply chain problems.
• You have a knack for answering open questions with data.
• You understand that simplicity is hard but key to achieving maintainability and to continually delivering value to the business.

• PhD or MS in Operations Research, Industrial Engineering, Computer Science, Mathematics, Statistics, Physics, or related quantitative fields.
• 3+ years of experience leading large‑scale implementations of optimization, simulation, machine learning, and deep learning modeling at scale.
• Demonstrated experience writing highly performant code and deploying algorithms in a production environment. Proficient in predictive and prescriptive algorithms.
• Proficient in one or more programming languages:
  Python, R, Kotlin, or Java.
• Expert at formulati ng and implementing mathematical models ranging from mixed‑integer programming, stochastic dynamic programming, and reinforcement learning.
• Experience in implementing advanced statistical techniques like regression, clustering, PCA, time series forecasting, etc.
• Proficient 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.
• Able to produce reasonable documents and narratives…