Kohl's: Staff Decision Scientist, Optimization


The Data Science team at Kohl’s develops advanced and scalable algorithms to power our online and in-store business. As a decision scientist, you will be working closely with other data scientists, software/machine learning engineers, product managers, designers within the same team, bridge data science and optimization techniques, and build products that enable the company to make intelligent data-driven decisions. Your primary focus will be applying various techniques from operations research to solve business problems. On top of that, you will also be working with techniques from machine learning, causal inference and statistics. The work for this position includes solving problems such as demand forecasting and inventory allocation, network flow optimization, assortment optimization, promotion and pricing, etc. The ideal candidate will have a strong technical and analytical background and be passionate to make big business impacts by partnering with business teams to develop and test strategic roadmap for products.


  • Excel at formulating optimization problems based on business objectives/constraints and solving them with commercial and open source optimization solvers/packages.
  • Collaborate with team members (Product Manager, Designer, Data Scientists, MLEs, Software Engineers) as well as stakeholders and end-users to identify, design, execute and interpret experiments to optimize performance and achieve desired business outcomes.
  • Communicate complex ideas and analyses to both technical and non-technical audiences.
  • Conduct ad hoc analysis to answer business questions and support strategic initiatives.


  • BS with 5+ years of experience (or MS with 2+ years) in Data Science, Computer Science, Machine Learning, Applied Mathematics, or equivalent quantitative field
  • Deep understanding of math programming techniques such as linear programming, integer programming, mixed-integer linear programming, nonlinear programming (convex, non-convex).
  • Experience with one or more of the commercial and open-source optimization solvers/packages like Gurobi, Pulp, Coin-OR, CPlex, XPress, GLPK, SciPy optimize etc.
  • Ability to understand business outcomes and translate them into actionable optimization solutions
  • Think in terms of iterative development, document, and communicate throughout products’ data science lifecycle.
  • Strong problem solving skills with an emphasis on product development.
  • Solid business acumen, with the ability to understand stakeholder/user needs and translate them into optimization solutions.
  • Experience proposing rapid experiments to test the effect of new strategies or initiatives, and iterate quickly.
  • Experience with SQL or other SQL-like data querying languages.
  • Experience with machine learning/statistical modeling (including Generalized Additive Models) and data analysis.
  • Proficient software development skills in languages such as Python, R, Scala.
  • Experience documenting, synthesizing, and communicating results at all levels of the organization.


  • Master’s Degree and/or Ph.D degree in Operations Research, Engineering, Mathematics, Computer Science, Statistics or other quantitative fields.
  • Experience in Supply Chain Optimization.
  • You have a proven record as a decision scientist who develops, optimizes, and scales models into a production environment.
  • You have a proven record of developing statistical/advanced machine learning models along with applying optimization and operations research techniques.
  • You have experience with Cloud technologies such as GCP, AWS, and Azure and distributed frameworks like Spark, TensorFlow, etc.