Head of Data Science

Seattle, WA /
Data Science /
Full Time
At Shelf Engine, we’re harnessing the power of AI to provide real-time, intelligent forecasting for food retailers like grocery stores, restaurants, and cafes across the United States. We’re able to drastically reduce the amount of shrink (food waste) which in turn drives profit for retailers, lowers costs for consumers, and reduces the ecological and social impacts of waste. We’re using technology to solve a globally-relevant problem that both creates a positive environmental impact and an exciting (and potentially massive) commercial opportunity.

We are hiring a Head of Data Science to join our growing technical team. You will work alongside our co-founders and lead our data science team, to develop continued excellence in our business. Your deep background in mathematics, statistics or econometrics, combined with your experience solving real world business problems, will directly impact the accuracy of our forecasting - reducing food waste and avoiding understocking situations. Help us solve critical problems in the food industry in the following areas: time-series demand forecasting, optimization, and feature/trend analysis.

As our Head of Data at Shelf Engine, you will:

    • Lead a team of Data Scientists to build a live forecasting system which accurately determines how much food to order at thousands of grocery stores across the country, drastically reducing food waste.
    • Build organizational capability in time series forecasting, optimization, and other disciplines relevant to solving Shelf Engine's business needs.
    • Work to deeply understand customer needs across the business, and build the infrastructure necessary to measure their performance, detecting anomalous forecasting situations and building plans to address them.
    • Work cross-functionally (e.g. Engineering, Operations, Customer Success, Sales, etc) to champion a strategy to frame problems, both mathematically and within the business context.
    • Design, analyze, and run both simulated and live experiments (A/B and multivariate tests) to drive KPI improvement.
    • Work hands on with the team, building mathematical and ML models, writing and reviewing production code, and using analysis and reporting to gain actionable insights in the business.

And we think you would make a great Head of Data Science if you:

    • Have a Masters or higher degree in a related quantitative field (Applied Math, Statistics, Econometrics, etc). 
    • Bring 8+ years of relevant working experience in data science, preferably with specific experience in the domain of time series forecasting and/or optimization.
    • Display strong leadership skills, with 3+ years of team management experience, and a strong ability to mentor and guide a small team of Data Scientists.
    • Have experience building and operating a live forecasting or other machine learning system in production.
    • Have production-level experience with data querying languages (e.g. SQL), scripting languages (e.g. Python).
    • Have expertise with statistical analysis, applying various machine learning techniques, especially predictive modeling, to solve business problems 
    • Bring a proven ability to think creatively, solve problems, learn quickly, work independently, handle ambiguity, and adapt to change in a fast-paced environment 
    • Possess excellent written, verbal, and interpersonal communication and presentation skills
About Us:
At Shelf Engine, you will join a small, powerful, customer-centric team that’s hungry for change in an untapped industry. Our founders are well versed in the food industry and have successfully built product and engineering teams. We’re not only solving complex technical problems at scale but tackling key initiatives with large environmental impacts as well. We're a tight-knit and passionate team that 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.