Staff Applied Scientist

Role overview

Join Afresh as a Staff Applied Scientist to lead R&D addressing perishable inventory control. You’ll use machine learning, forecasting, operations research, and stochastic optimization to improve Afresh’s core replenishment system and reduce food waste.

Key missions

• Lead R&D for core replenishment improvements in areas including:
  • Modeling consumer demand and complex supply chains
  • Applying operations research and stochastic optimization
  • Improving inventory control and replenishment decisions under uncertainty
• Research, implement, and validate enhancements to the replenishment system using rigorous evaluation.
• Set technical direction for the replenishment R&D roadmap across:
  • Demand forecasting
  • Inventory optimization
  • Decision-making policy

Requirements

• Experience researching and building systems for large-scale decision making under uncertainty.
• Ability to clearly communicate complex mathematical ideas to product teams and translate business needs into constrained optimization problems.
• Strong capability to independently deliver high-quality software implementations in the Python data stack (e.g., NumPy/PyTorch/Pandas).
• MS or PhD in Operations Research, Industrial Engineering, Computer Science, Electrical Engineering, or another quantitative field (or equivalent practical experience).
• Industry experience level:
  • MS: 8+ years
  • PhD: 4+ years

Nice to have

• Understanding of an ML platform and passion for mentorship.