Note: The job is a remote job and is open to candidates in USA. Afresh is an AI platform for grocery that aims to reduce food waste and improve inventory management for grocers. The Staff Applied Scientist will lead R&D efforts to develop and enhance AI/ML models for replenishment technology, tackling complex challenges in inventory control and decision-making.
Responsibilities
- Set technical direction for core replenishment R&D — define the modeling roadmap across demand forecasting, inventory optimization, and decision-making policy, and align it with product and business strategy
- Model complex problems such as inventory decay, promotions, price elasticity, and inventory uncertainty, and implement solutions to multi-stage and multi-echelon inventory optimization problems
- Drive fundamental changes to our core system from research through production, writing rigorously tested and scalable code — we are not an analytics team
- Lead research and development for new product and business challenges
- Raise the technical bar across the Intelligence team: mentor scientists and engineers, set standards for experimental rigor, and review designs and results
- Push the boundaries of AI capabilities in both products and scientist workflows
Skills
- 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
- Excellent communication and presentation skills. You should be able to explain complex mathematical ideas to product teams in plain English and easily translate business requirements into constrained optimization problems
- Ability to independently deliver high quality software implementations of your solutions in the Python data stack (numpy/torch/pandas/etc). Prior experience with Python is not required
- 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
- Nice to Have skills: understanding of ML Platform and a passion for mentorship
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.
- Meaningful equity (U.S. employees).
- 401(k) program with a generous company match.
- Home office stipend.
- "Coworking Wallets" for flexible workspace access.
- Annual professional development budget to master new skills and grow their career at Afresh.
- Monthly stipends for "Betterment" (wellness/lifestyle) and telecommunications.
- Flexible paid time off to take the time you need to recharge.
- Full-time U.S. employees are eligible for these benefits.
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