Data Scientist - Global AI

at  HelloFresh

At HelloFresh, we want to change the way people eat forever by offering our customers high-quality food and recipes for different meal occasions. Over the past 10 years, we’ve seen this mission spread around the world and beyond our wildest dreams. Now, we are a global food solutions group and the world’s leading meal kit company, active in 18 countries across 3 continents. So, how did we do it? Our weekly boxes full of exciting recipes and fresh ingredients have blossomed into a community of customers looking for delicious, healthy, and sustainable options. The HelloFresh Group now includes our core brand, HelloFresh, as well as: Green Chef, EveryPlate, Chefs Plate, Factor_, and Youfoodz.
Come see what’s cookin’ at HelloFresh!
At HelloFresh, we want to revolutionize the way we eat by making it more convenient and exciting to cook meals from scratch. We have offices all over the world and we deliver delicious meals to millions of people. We are the industry leader in meal-kit subscription services and we’re growing all the time. We have distinct meal-kit services that cater to everyone with the most menu variety in the market, which allows us to reach an incredibly wide population of people. The HelloFresh team is diverse, high-performing, and international, and our work environment is an inspiring space where you can thrive as a result.
We are building our Customer Value Forecasting squad inside the Global AI department to develop better Marketing and Product facing machine learning products faster. The Global AI team works cross-functionally to identify opportunities to build and deploy advanced ML solutions throughout the organization and works closely with Data Scientists, ML engineers, and Data Engineers to build and maintain best-in-class data products to improve HelloFresh’s user experience.

You will…

• Maintain relationships with key stakeholders on the Growth Marketing, Finance and Operations, and Product teams.
• Be embedded in a team with Machine Learning Engineers, Data Engineers, and Analysts to build valuable machine learning-driven products.
• Design and Maintain Statistical and Machine Learning Models in order to drive strategic guidance on budget allocation, forecasting and capacity planning.
• Formalize hypotheses about how forecasts are expected to evolve, identify any outliers, develop methods to deal with outliers
• Derive key insights and influence stakeholders on strategy and planning
• Develop scalable solutions for forecasting and work closely with Data and Machine Learning Engineering to put them into practice.
• Explore and analyze data sources and processes to identify opportunities to improve our forecasting practices.

At a minimum, you have…

• Bachelor’s degree in data science, computer science, statistics, engineering or a related field
• Experience in building and validating machine learning models including gradient boosted trees, generalized linear regression, and time series.
• Strong mathematical and statistical understanding of machine learning techniques and their uncertainty analysis.
• Ability to perform data analysis in Python; proficiency using SQL.
• Ability to communicate complex analyses to both technical and non-technical stakeholders.
• Ability to pick up new technologies and modelling methodologies quickly while solving actual business problems.
• Interest in working with modern data science tooling such as cloud development, version control, CI/CD, Docker, model registries and a feature store.

You’ll get…

• Competitive Salary & 401k company match that vests immediately upon participation
• Generous parental leave of 16 weeks & PTO policy
• $0 monthly premium and other flexible health plans effective first day of employment
• 75% discount on your subscription to HelloFresh (as well as other product initiatives)
• Snacks, cold brew on tap & monthly catered lunches
• Company-sponsored outings & Employee Resource Groups
• Collaborative, dynamic work environment within a fast-paced, mission-driven company

New York Pay Range

Please refer the Job description for details