Senior Data Scientist, Growth Alliance

HelloFresh's HelloTech organisation is a global technology backbone of more than 1000 people, building digital products that power end-to-end food experiences including meal kits, ready-to-eat meals, and specialty offerings. The company operates subscription-based, direct-to-consumer brands united by shared platforms, data, and operational excellence.

• 5+ years of professional experience in data science, machine learning, or a related quantitative field with successful production model deployment.
• Proficiency in Python and experience with modern ML stacks including Databricks, Spark, and MLflow.
• Strong foundation in machine learning for personalization, including hands-on experience with reinforcement learning and contextual bandits (e.g., Thompson Sampling, epsilon-greedy).
• Solid understanding of experimentation and causal inference with experience designing and analyzing controlled experiments.
• Skilled in classical ML techniques such as regression, classification, clustering, and recommendation systems.
• Experience working with customer behavior data, segmentation, and production feature pipelines.
• Clear, structured communication and collaborative, cross-functional mindset.

Nice to have:

• Experience with off-policy evaluation, counterfactual learning, propensity methods, or sequential testing (SPRT).
• Familiarity with experimentation platforms (e.g., Statsig) and streaming/low-latency inference.
• Experience handling unstructured data (embeddings, text signals) as model features.
• Exposure to marketing/CRM decisioning, deliverability, or funnel/conversion optimization.

• Build, own, and iterate on reinforcement learning and machine learning models running in production for high-traffic conversion and communication flows.
• Develop decisioning logic for optimizing messaging lifecycle and funnel next actions.
• Drive architectural evolution of contextual-bandit systems toward offline policy evaluation and low-latency inference.
• Partner with engineering for system design to integrate models into funnel and messaging architecture.
• Own experimentation design for decisioning models, defining success metrics, guardrails, and interpreting results with rigorous statistical methods.
• Monitor and maintain model safety, effectiveness, data reliability, and latency in production.
• Collaborate with CRM operations, marketing analytics, and platform teams to translate model behavior into trusted marketing decisions.