Afresh is on a mission to eliminate food waste and make fresh food accessible to all. Our first A.I.-powered solution optimizes ordering, forecasting, and store operations for fresh food departments in brick-and-mortar grocers. With our Fresh Operating System, regional and national grocery retailers have placed $1.6 billion in produce orders across the US and we've helped our partners prevent 6.9 million pounds of food from going to waste. Working at Afresh represents a one-of-a-kind opportunity to have massive social impact at scale by leveraging uncommonly impactful software – we hope you'll join us!
About the role
The Modeling and Optimization team builds Afresh's 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! 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.
You will be working on pushing the boundaries of our system's performance on product categories we're already live in, as well as expanding our product to entirely new categories. You will be responsible for implementing new systems end-to-end, including working with product teams to define the business needs of a solution, reviewing research papers and implementing novel ideas, and scaling up experiments to generate predictions and decisions on millions of items every day. 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.
Are you someone who loves digging into messy data and rigorously and irrefutably illustrating the story underneath the numbers? Are you excited about experimentation, balanced groups, statistical power, answering questions that drive the strategy of the company, and uncovering opportunities no one else thought of leveraging data?
We are looking for a seasoned Product Data Scientist to kick start our Data Science team at Afresh. You will be part of the team that helps uncover features and key opportunities for improvements in our core recommendation model, sets success metrics to guide product development, investigates data quality issues, and leads A/B testing and experimentation analysis. As one of the first members of team, you will be a key player in driving the direction of the team.
Skills and experience
We are looking for a Data Scientist with relevant and demonstrated industry experience working across a large scope with multiple cross functional partners and driving multiple team projects to success. They would also ideally have experience using the following software/tools:
The above represents attributes our ideal candidate possesses. We encourage all highly qualified candidates to apply, even if they do not fulfill all the listed criteria.
Founded in 2017, Afresh is working on the #1 solution to curb climate change: reducing food waste. By combining human insight and transformative technology, we're helping grocers provide fresher food to customers at more affordable prices.
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 we've raised over $148 million in funding from investors including former co-CEO of Whole Foods Market Walter Robb and Eric Schmidt's Innovation Endeavors.
Fresh 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.
Afresh provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity/expression, marital status, pregnancy or related condition, or any other basis protected by law.
A qualified candidate must reside in or be willing to relocate to one of these states to be considered: AR, CA, CO, FL, GA, IL, KY, MA, MI, MT, MO, NV, NJ, NY, NC, OR, PA, TX, WA, WI