Data Science Manager

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At Shelf Engine, our mission is to reduce food waste through automation. We harness the power of AI to provide real-time, intelligent forecasting and fully automated ordering to food retailers across the United States. We’re able to drastically reduce the amount of food waste generated while simultaneously maximizing sales and expanding margins for grocers—a triple win for suppliers and retailers, consumers, and the environment.

Shelf Engine is looking for a talented Data Science Manager to join our growing team and report to our Head of Data Science. In this role, you will work with multiple teams across functions to solve sophisticated supply chain problems using a complex array of machine learning, forecasting, inventory, optimization, and other models. The goal is to help Shelf Engine grow fast in machine learning R&D, machine learning engineering, and ML OPs. You’ll accomplish this by being a hands-on technical manager and developing best-in-class AI products. 

This position is based in Seattle, WA or remote

As a Data Science Manager at Shelf Engine, you will: 

  • Lead a team to enhance and maintain a production machine learning system at scale
  • Manage and deliver on high-quality end-to-end solutions in your domain
  • Work cross-functionally with Engineering and customer-facing teams 
  • Continuously improve the quality and accessibility of our data science capabilities 
  • Provide technical expertise to continuously improve our product 
  • Mentor and provide professional development to direct reports

What we are looking for in a candidate: 

  • You embrace our company principles: make the first move, make better decisions, be furiously curious, commit and deliver, have empathy, invent solutions, be authentic
  • You have 5-7+ years industry experience some combination of:
    • Experience putting models into production or with a live online system 
    • Experience working with big data (e.g. SQL, Spark)
    • Experience with performance monitoring and automated alerting 
    • Experience with production ML tooling (e.g. Airflow, Databricks, Azure, AWS, or GCP)
  • 2+ years of management experience
  • Experience leading data scientists and growing teams  
  • An attitude that is collaborative, collegial, and passionate about impact
  • Eagerness to work at a rapid growth start-up
  • You have a Bachelor’s or Master’s degree in a STEM field
  • You are authorized to work in the U.S. for any employer

What Shelf Engine offers you: 

  • A unique opportunity to join a fast-growing sustainability startup early on, making a meaningful impact on the team as well as the environment
  • An inclusive work environment that emphasizes each team member’s personal and professional growth
  • Competitive salary in the range of $175,000 to $215,000, depending on skills and experience, in addition to a bonus component 
  • Pre-IPO equity with a four-year vesting schedule
  • PTO that is unlimited and self-managed for full-time employees
  • 100% employer-paid premiums for medical, dental, and vision insurance for employees, and 50% covered for eligible dependents
  • Coverage for life insurance, short- and long-term disability, and access to a robust Employee Assistance Program
  • Optional employee contribution of pre-tax dollars to medical and dependent care FSA accounts
  • 401k plan through Guideline to contribute to your financial future
  • Seattle only: Company-paid ORCA transit card

Please note, employees will need to provide proof of vaccination in order to access any of our offices or to attend company events.

About Us:

At Shelf Engine, you will join a team of driven, passionate, and caring people hungry to make change in an untapped industry. We’re not only solving complex technical problems at scale but also tackling key initiatives with significant environmental impacts. Our team is determined to disrupt a massive industry and leave behind a positive legacy for generations to come.

Shelf Engine is an equal opportunity employer and does not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

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