Senior Applied Scientist (Store Solutions)

The Afresh Intelligence team is responsible for the development and performance of AI/ML models that power our core replenishment technology. Our models are directly responsible for ordering millions of dollars of fresh inventory across the world every day. Fresh food ordering is an extremely complex high-dimensional decision-making problem, and we face the complex challenges presented by decaying product, uncertain shelf lives, varying consumer demand, stochastic arrival times, extreme weather events, and tight performance constraints (to name a few). We tackle these problems with a mix of machine learning, large-scale simulation, and optimization technologies.

We are looking for a Senior Applied Scientist to drive R&D work at Afresh. You will take your existing knowledge of machine learning, forecasting, operations research, and stochastic optimization and apply it to the challenging and important problem of perishable inventory control. You will research, implement, and rigorously validate improvements to our core replenishment system. This will include modeling consumer demand, item-level perishability, and complex multi-echelon supply chains. Your work will be visible from day one, will make a substantial impact on decreasing food waste, and will lead to fresher, healthier produce for millions of people across the world.

• →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.
• →Advance 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.

• 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, 4+ years of industry experience; for candidates with a PhD, some industry experience preferred.
• Experience researching and building systems that support large-scale decision making under uncertainty.
• Prior experience or academic knowledge 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. 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.
• Nice to Have skills: understanding of ML Platform and a passion for mentorship

Salary Range in U.S.: $173,000 - $234,000 + meaningful early-stage equity + benefits

Founded in 2017, Afresh is using AI to tackle the #1 solution to curb climate change: reducing food waste. By building AI specifically for the intricacies of grocery—from the fresh perimeter to the center store—we help grocers minimize waste and maximize sales.

Afresh sits at an incredible intersection of positive social impact, rocket ship financial growth, and cutting-edge technology. Our best-in-class AI research has been published in top journals, including ICML, and our investors include Al Gore’s Just Climate, former Whole Foods Market CEO Walter Robb, and Eric Schmidt's Innovation Endeavors.

Grocery is the past, present, and future of our food system – the waste we create today will impact our planet for years to come. Join us as we continue to build a vibrant, diverse, and inclusive team that embodies our company’s values of proactivity, kindness, candor, and humility.

Here at Afresh, many of our employees work remotely provided that they reside in one of the following states: AL, AR, CA, CO, FL, GA, IL, KY, MA, MI, MT, MO, NV, NJ, NY, NC, OR, PA, TX, WA, UT, VA, WI.