Senior Data Scientist, Growth Alliance (f/m/x)

HelloFresh is a company operating in food subscription and meal kit delivery with a global technology backbone called HelloTech employing over 1000 people. HelloTech builds digital products that power the end-to-end food experience from customer apps to supply chain optimization. The Growth Alliance team focuses on marketing engine aspects such as media investment, conversion funnel, and personalized customer communication in a subscription-based direct-to-consumer model.

• Proven track record of scientific work with a Bachelor's, Master's, or PhD in statistics, physics, economics, mathematics, data science, or related quantitative field.
• Minimum 3 years of professional experience as a senior data scientist or similar quantitative role, preferably in e-commerce, marketing, or high-traffic consumer environments.
• Strong marketing and/or growth domain knowledge with experience applying statistical models such as regressors and classifiers.
• Fluency in Python and its scientific stack (NumPy, pandas, scikit-learn, Matplotlib).
• Proficient in retrieving and analyzing data with SQL.
• Familiarity with software engineering practices and tools such as Git, Docker, and cloud environments like AWS.
• Experience with Databricks and Spark is a plus.
• Comfortable using recent Generative AI tools in solution design.
• Critical thinker and creative problem solver with ability to prioritize solutions based on impact.
• Excellent communication skills and ability to collaborate internationally across diverse stakeholders.

• Design, build, and take ownership of statistical and machine learning models from data collection to production, aligning with non-technical stakeholders.
• Collaborate within cross-functional teams including engineering, product, and marketing to translate business objectives into data-driven strategies.
• Design experiments, define success metrics and guardrails, and interpret results accounting for statistical uncertainty, noise, and bias.
• Continuously monitor and refine model performance, data reliability, and drift in production.
• Retrieve, manipulate, and analyze large heterogeneous datasets and build supporting data pipelines.
• Proactively identify improvements for data products delivered to stakeholders.
• Support and coach junior data scientists as a senior team member.