Tuesday, 13th February 2024, Job by HelloFresh, GreenTodays :
Job Summary
- Published on: Tuesday, 13th February 2024
- Designation: Data Science Manager - Global ML&AI,
- industry: Miscellaneous
- Vacancy: 1
- Employment Status: Full-time
- Job Location: Saint Louis, MO
- Salary: 0
- Gender:
- Application Deadline: Tuesday, 13th February 2024
Job Description
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.The Decisions Alliance's goal is to enable HelloFresh to build a rapid feedback loop around understanding our customers, finding the best way to communicate with them and utilizing AI/ML capabilities. We're responsible for the company's Communications, Customer Data, Experimentation, and MLOps Platforms. Our team works on a variety of technologies ranging from high throughout, real-time communications systems to deep statistical libraries to large-scale machine learning training pipelines.
Responsibilities + Skills
Snacks, cold brew on tap & monthly catered lunchesCompany-sponsored outings & Employee Resource GroupsCollaborative, dynamic work environment within a fast-paced, mission-driven company
Education
Experience in solving machine learning problems with modern machine learning software stack (Python, Tensorflow, Pytorch, Spark) as well as modern machine learning algorithm stack (Transformers, Graph Neural Networks, boosted decision trees, GenAI, statistical inference)Familiarity with cloud development environments (AWS, Azure, GCP)Solid grasp of advanced statistical concepts (e.g., Bayesian statistics; multilevel and generalized linear models; timeseries; bootstrapping)
Experience