Staff Applied Scientist, Afresh Technologies

Salary not provided
SQL
Python
Pandas
PyTorch
Senior level
Remote in US
San Francisco Bay Area
Toronto

More information about location

Afresh Technologies

SaaS for grocery store operations

Open for applications

Afresh Technologies

SaaS for grocery store operations

101-200 employees

RetailB2BArtificial IntelligenceSustainabilityFoodLogisticsSaaS

Open for applications

Salary not provided
SQL
Python
Pandas
PyTorch
Senior level
Remote in US
San Francisco Bay Area
Toronto

More information about location

101-200 employees

RetailB2BArtificial IntelligenceSustainabilityFoodLogisticsSaaS

Company mission

To eliminate food waste and make fresh food accessible to all.

Role

Who you are

  • 5+ years of industrial or academic experience building mission-critical applied systems
  • Excellent communication and presentation skills. You should be able to explain complex mathematical ideas to product teams in plain English
  • 5+ years of experience with Python libraries like (Pytorch or Ray)
  • Fluent in programmatic data analysis using SQL and Pandas
  • Excellent data visualization skills
  • You will thrive in this role if you love to work on applied, open-ended problems in research and production environments: thorough error analysis, deep understanding of the data you are modeling, feature selection, algorithm implementation, hyperparameter optimization, deployment, and production 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

What the job involves

  • As an Applied Scientist at Afresh focused on inventory, you will take your existing knowledge of machine learning, operations research, or statistics and apply it to the challenge of inventory estimation for perishables
  • Your will research, implement, and rigorously validate improvements to our core inventory system
  • This will include modeling inventory counts provided by our users, incoming shipments, sales, and outflow due to spoilage
  • 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
  • You will work on improving the accuracy and calibration of our probabilistic inventory models that power our store-level ordering products. You will also lead research development for new product and business challenges
  • In your first 3 months, you will acquire a comprehensive understanding of our current inventory system and modern computational approaches to large scale simulation. You will gain proficiency in our data manipulation, transformation, and estimation, and you'll test an experimental improvement to our inventory system
  • By the end of your first 6 months, you will have proposed, implemented, and rigorously validated an improvement to either inventory estimation, inventory count targeting, or food waste measurement
  • By the end of your first year, you will have led the implementation of fundamental changes to our core inventory system and led research into extensions like anytime inventory reporting
  • We need to make optimal ordering decisions for millions of items for weeks at a time, and our system must be fault-tolerant to an extreme. Our partners rely on our system to order millions of dollars of inventory every week, and so your code must be rigorously validated, tested, and bug-proof

Our take

Antiquated inventory management systems are detrimental to grocers money and time. Generalized and paper-based systems result in the over-purchase of stock, and this results in waste of fresh food and financial budgets.

Afresh has created an operating system designed specifically to manage inventory and sales of fresh food. The system is powered by AI to help provide forecasting and analysis of inventories, helping grocers stock more economically and thus waste less fresh food.

The company has grown rapidly in recent years, and they have now partnered with over 3,000 stores in 40 states across the US. Clients include Albertsons, WinCo Foods, Heinen's, Save Mart, Bashas, and Cub Foods.

Freddie headshot

Freddie

Company Specialist

Insights

Top investors

Few candidates hear
back within 2 weeks

6% employee growth in 12 months

Company

Funding (last 2 of 5 rounds)

Aug 2022

$115m

SERIES B

Nov 2020

$13m

SERIES A

Total funding: $147.8m

Company benefits

  • Comprehensive health plans
  • Competitive compensation
  • Generous parental leave
  • Equity packages
  • 401k matching
  • Flexible vacation policy
  • Monthly grocery stipend
  • Professional development program
  • Monthly physical / mental health stipend
  • Work from home stipend

Company values

  • Humility - We serve our customers and teammates, and listen to their needs—especially those who don’t look or live like us
  • Proactivity - We identify opportunities, own problems, and act with purpose to keep moving forward
  • Candor - We believe feedback makes us better and value transparent communication
  • Kindness - We care for the entire person and work to create an environment where people feel welcome.

Company HQ

Yerba Buena, San Francisco, CA

Founders

Matt Schwartz

(Co-Founder & CEO)

Worked as a consultant for Bain before going on to pursue their passion for food systems. They also previously founded Statfoods.

Volodymyr Kuleshov

(Co-Founder & Chief Technologist)

Has a PhD in computer science from Stanford. Alongside Afresh, they are an assistant professor in the technology department at Cornell.

Nathan Fenner

(Co-Founder)

Has a Bachelors, Masters and MBA from Stanford University. Post studying, they became a Lecturer at Stanford in the Mechanical Engineering department before working at liquid robotics.

Salary benchmarks

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Diversity & Inclusion at Afresh Technologies

  • We’re building belonging
  • Diverse perspectives and backgrounds are critical to achieving our mission. We’re creating a workplace where everyone belongs, and team members feel empowered to make a difference while living and working as their authentic selves

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