Set technical direction for core replenishment R&D.
Model complex problems such as inventory decay, promotions, price elasticity, and inventory uncertainty.
Drive fundamental changes to our core system from research through production.
Lead research and development for new product and business challenges.
Mentor scientists and engineers, set standards for experimental rigor.
Requirements
MS or PhD in Operations Research, Industrial Engineering, Computer Science, Electrical Engineering, or another quantitative field, or equivalent practical experience.
For candidates with an MS, 8+ years of industry experience; for candidates with a PhD, 4+ years of industry experience.
Experience researching and building systems that support large-scale decision making under uncertainty.
Prior experience in areas such as inventory optimization, supply chain management, network optimization, forecasting, game theory, decision analysis, stochastic optimization, approximate dynamic programming, or related fields is a plus.
Excellent communication and presentation skills.
Ability to independently deliver high quality software implementations of your solutions in the Python data stack (numpy/torch/pandas/etc).
Tech Stack
Numpy
Pandas
Python
Benefits
Comprehensive medical, dental, and vision coverage for you and your family, with the majority of premiums covered by Afresh.
Dedicated mental health support and counseling services.
Competitive base salary, meaningful equity (U.S. employees), and a 401(k) program with a generous company match.
Home office stipend and "Coworking Wallets" for flexible workspace access.
Annual professional development budget to master new skills and grow your career at Afresh.
Monthly stipends for "Betterment" (wellness/lifestyle) and telecommunications.