Tech Stack

Description

In this role, you will design and deploy large-scale recommender systems for HelloFresh's menu personalization, directly impacting customer experience and business growth. You'll work with a team of data scientists and engineers to build and improve personalized recommendation algorithms across global markets, using a modern tech stack and A/B testing to drive data-driven decisions.

Requirements

• Proven track record (Bachelor's, Master's, or PhD) in computer science, statistics, physics, economics, mathematics, or data science
• 3+ years of experience as a data scientist developing and deploying recommender systems or personalized ML models in production
• In-depth knowledge of various recommendation algorithms and techniques
• Experience with state-of-the-art technologies like AWS, Kafka, PySpark, Airflow, Databricks, MLFlow
• Strong collaboration and communication skills to work with cross-functional teams

Responsibilities

• Contribute to designing and implementing next-generation recommender models from experimentation to operationalization
• Propose new personalization approaches and evolve statistical and ML models in line with company strategies
• Design and execute A/B tests to measure impact of new recommendation strategies on key metrics
• Collaborate with data engineering, backend engineering, ML engineering, and product to translate business objectives into concrete strategies
• Analyze model performance to understand customer behavior and implement technical improvements