Data Analysis, Data Visualization, Forecasting, JAX framework, Machine learning techniques, Pandas, PyTorch, SQL, TensorFlow
About the Role
The Prediction, Optimization, and Planning (POP) team builds Afresh's core replenishment technology. Our AI 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. Our team has presented work at multiple industry leading conferences, and we encourage team members to write and present their work publicly.
As an Applied Scientist at Afresh focused on forecasting, you will take your existing knowledge of machine learning and apply it to the challenge of demand forecasting. You will thrive in this role if you love the craft of neural networks in research and production environments: hyperparameter optimization, model tuning, feature selection, thorough error analysis, architecture selection, and deep understanding of the data you are modeling. We are looking for someone who is equally adept at gaining insights from 8 hours of data analysis or 8 hours of reading papers.
Your will research, implement, and rigorously validate improvements to our core forecasting system. This will include modeling seasonal demand, rare events, promotion cannibalization, and aggregating correlated demand across multi-echelon systems. 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.
Skills and Experience
Salary Band:
LI-REMOTE
$186,000 - $212,000
About Afresh
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.
Afresh is on a mission to reduce food waste and increase access to nutritious food globally by transforming the fresh food supply chain. Our AI-powered solutions optimize the multi-trillion-dollar grocery industry's food ordering, production, and merchandising processes. We built the first platform capable of handling all of Fresh food’s complexities.