Senior Applied Data Scientist, Supply Chain Optimization

What you'll do

• Develop and manage state-of-the-art predictive and prescriptive algorithms to automate and optimize supply chain decisions.
• Write high-performant, scalable Python code for production environments involving millions of combinations of SKUs.
• Design and implement mathematical models including mixed-integer programming, stochastic dynamic programming, and reinforcement learning.
• Collaborate with engineers to deploy optimization and machine learning algorithms at scale.
• Develop advanced statistical techniques such as regression, clustering, PCA, and time series forecasting.
• Build internal data tools and production datasets using SQL or Hive for research and experimentation.
• Translate complex data into actionable insights through visualizations and narratives for business partners.
• Improve engineering standards, tooling, and processes to ensure codebase maintainability and reliability.

What we're looking for

• PhD or MS in Industrial Engineering, Operations Research, Computer Science, Applied Mathematics, Statistics, Physics, or a related quantitative field.
• 3+ years of experience leading large-scale implementations of optimization, simulation, machine learning, and deep learning at scale.
• Extensive experience writing highly performant Python code and deploying algorithms in a production environment.
• Proficiency in predictive and prescriptive algorithms 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 data tools using scripting languages like Python.
• Strong communication skills to translate data into actionable insights through visualizations and narratives for business partners.