About us:

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.

A role with Target Data Science & Engineering means the chance to help develop and manage state of the art predictive algorithms that use data at scale to automate and optimize decisions at scale. Whether you join our Statistics, Optimization or Machine Learning teams, you’ll be challenged to harness Target’s impressive data breadth to build the algorithms that power solutions our partners in in Marketing, Supply Chain Optimization, Network Security and Personalization rely on.  

As a Director Data Science, you’ll be Responsible for leading Target’s efforts on the Mathematics of Optimization for Supply-Chain with a focus on IPC (Inventory Planning & Control). This role is responsible for driving work direction to others and will work directly with the business to solve business problems.  This role will solve the problem of identifying the optimal positioning of inventory, given as input a network topology and the probability distributions of guest demand for each SKU on each channel of sale. This involves solving a multi-echelon stochastic optimization problem that leverages the full power of the mathematical/computational apparatus we have developed for Markov Decision Processes.

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

About you:
• M.S. or Ph.D. in math, advanced statistics, physics, bio statistics, bio science, operations research or computer science
• Strong academic credentials in Mathematics - well-trained in Math foundations (specifically in Probability Theory, Real Analysis, and Linear Algebra)
• 7+ years of experience deploying algorithms in a production environment
• 5+ years of experience in Supply Chain Optimization Science
• Deep understanding of the Supply Chain operational details as well as the mathematics of supply chain, particularly in stochastic optimization
• Must have strong written and oral communication skills, and the ability to debate proposed ideas from both a business perspective and from a mathematical perspective.