Lead Data Scientist (Remote)

About Target
At Target, we help families discover the joy of everyday life. That mission is brought to life through our strong values, inclusive culture, and purpose-driven work.

About the Role
As a Lead Data Scientist on the Supply Chain Optimization team, you’ll use data science to power smarter decision-making across one of the most complex retail supply chains in the world. You’ll design and implement advanced predictive and prescriptive models using operations research, machine learning, and simulation to optimize areas like inventory, transportation, sourcing, distribution, and fulfillment.

You’ll develop scalable, high-performance algorithms and work closely with engineers to productionize models that impact millions of product combinations across our distribution networks—running multiple times per day. This work directly supports automation, efficiency, and business intelligence throughout Target’s operations.

In this role, you’ll also collaborate with business stakeholders to understand retail processes, refine model granularity and performance, and ensure that technical solutions are usable, reliable, and impactful. You’ll help define engineering standards, improve tooling, and mentor fellow data scientists and engineers. Our environment is fast-paced and agile, with the backing of Target’s vast resources and commitment to learning and innovation.

Who We’re Looking For
You’re a strategic thinker and strong communicator who thrives at the intersection of deep technical expertise and real-world application. You have a passion for clean, maintainable code, and enjoy working with large-scale data to solve complex problems.

We’re seeking someone who brings:

• Strong knowledge of supply chain domains including inventory, logistics, sourcing, and planning.

• A deep understanding of computer science fundamentals—data structures, algorithms, and information retrieval.

• Proficiency in writing performant, testable Python code (or similar languages like R, Kotlin, or Java).

• Hands-on experience deploying models in production environments and working with large datasets using tools like SQL or Hive.

• Familiarity with predictive and prescriptive modeling, and techniques such as regression, clustering, PCA, and time-series forecasting.

• The ability to clearly communicate insights through data storytelling, visualizations, and documentation.

• A strong sense of usability and empathy for business users who interact with data products.

• A collaborative spirit with the ability to work effectively across teams and time zones.
  

Qualifications

• A 4-year degree in a quantitative discipline (STEM) or equivalent work experience.

• PhD or MS in Operations Research, Industrial Engineering, Computer Science, Statistics, Mathematics, or a related quantitative field is strongly preferred.

• 5+ years of experience leading large-scale supply chain optimization, simulation, or machine learning efforts.

• Demonstrated success in deploying performant, scalable models in production environments.

• Experience with data architecture, model performance tuning, and iterative experimentation.

• Strong documentation and communication skills, especially in translating insights into business impact.

• Self-driven, detail-oriented, and able to work under tight timelines.
  

Work Location Flexibility
This position may be eligible for a Remote or Hybrid work arrangement, depending on Target’s business needs.

• In a Remote arrangement, you’ll work full-time from home or an alternate location (not a Target office) and may travel to headquarters up to four times per year.

• In a Hybrid (internally known as “Flex for Your Day”) model, you’ll work either remotely or onsite at a Target location based on your role, team needs, and daily tasks.