At Shelf Engine, our mission is to reduce food waste through automation. We harness the power of AI to provide real-time, intelligent forecasting for food retailers, suppliers, and food service companies across the United States. We’re able to drastically reduce the amount of food waste which in turn drives profit for our customers, lowers costs for consumers, and reduces the negative ecological and social impacts of waste.
We are excited to invite applicants for the role of Senior Data Scientist to report directly to our Head of Data Science. As part of the Data Science team, you will research, build, and launch new algorithms and solutions to solve complex problems for a rapidly evolving product. The goal is to help Shelf Engine develop best-in-class machine learning and advanced statistical models to achieve business objectives. If you have a passion for problem-solving, working collaboratively with a great team of data scientists and engineers, and making a huge social impact, this may be your dream job.
This position is based in Seattle, WA, or remote.
As a Senior Data Scientist at Shelf Engine, you will:
- Research, build, and launch machine learning and advanced statistical models to solve complex problems
- Be part of a highly collaborative and supportive Data Science team
- Provide technical mentorship and expand training to improve data science best practices
- Design, analyze, and interpret the results of experiments
- Communicate project results to a range of internal audiences
- Work closely with Product, Engineering, Operations, and customer-facing teams to identify problem areas and develop robust, scalable solutions
- Embrace our company principles through inclusive, authentically-kind, and empathetic interactions with our team and our customers
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
- 2+ years of industry experience with some combination of:
- Experience putting models into production or with a live online system (code quality, testing, monitoring)
- Experience working with big data and standard tooling (e.g. Python, SQL, Spark)
- Experience with performance monitoring and automated alerting
- Experience with production ML tooling (e.g. Airflow, Databricks, Azure, AWS, or GCP)
- You have experience in advanced machine learning (e.g., SVM, Random Forest, Bayesian inference, neural networks, etc), statistics, experimentation, and optimization
- You have a Masters or PhD degree in a STEM field
- You are authorized to work in the U.S. for any employer
- Nice to have: experience building supply chain or inventory management solutions
What Shelf Engine offers you:
- This 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 $140,000 to $180,000 depending on skills and experience
- 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.
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.