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Staff Data Scientist - San Francisco California
Company: Afresh Location: San Francisco, California
Posted On: 04/27/2024
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 34 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: You will act as the technical lead for our Data Science team. The Data Science team sits in our larger Machine Learning organization. The Afresh system comprises, among other sources of data, machine learning forecasts, inventory estimates, user-provided data, and clickstream data. You will work with product managers, go-to-market experts, applied scientists, and other stakeholders to turn this data into metrics and experiments that will guide our company towards more and more food waste reduction. You will also own a critical part of Afresh's business: proving the value that we generate for our customers. To do so, you will build on our existing statistical analysis tools to ship rigorous metrics and statistical experiments that demonstrate our impact to our customers and internal teams. - In your first 3 months, you will familiarize yourself with our existing statistical toolkit and make a scoped improvement to it. You will learn about our ongoing product experiments and metric development, and work with our data scientists to spin up an experiment and/or new metric. You will attend calls with our customers and learn about the nature of data in the grocery industry.
- By the end of your first 6 months, you will introduce additional metrics and ways of slicing at our data that unlock new insights for our customers. You will have onboarded onto our experimentation platform and helped guide our product team towards the right feature choice.
- By the end of your first year, you will make foundational improvements to our causal inference pipelines, making them more scalable and powerful. You will introduce new norms to the team around metric creation and statistical methods.
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