Senior Data Scientist (m/f/d)

About the role

As a Senior Data Scientist, you will play a key role in building production-grade data science and machine learning solutions that directly influence critical business decisions and customer experiences.

You will work on one of our high-impact products, partnering closely with product, engineering, and business teams. Rather than focusing on isolated analyses, you will be involved in products end to end — from problem framing and data quality to modeling, deployment, and ongoing monitoring in production.

This role is designed for a strong generalist who enjoys working across domains, applying solid statistical and machine-learning foundations to real-world problems, and turning ideas into reliable systems.

About your tasks

• Work in a product with colleagues from our Data & AI department and collaborate closely with product managers, engineers, and domain experts to translate business problems into data-driven solutions.
• Design, build, and operate end-to-end data science and machine learning solutions, from initial problem definition to production and iteration.
• Work hands-on with complex, real-world datasets, addressing challenges such as data quality, missing data, bias, and changing data distributions.
• Develop, evaluate, and improve statistical and machine-learning models, making well-reasoned trade-offs between model complexity, performance, scalability, and maintainability.
• Design and analyze A/B tests and experiments, including hypothesis definition, metric selection, statistical evaluation, and interpretation of results.
• Define and implement robust evaluation frameworks, including appropriate baselines, metrics, and validation strategies.
• Support bringing models into production using our cloud-based stack and ensuring they are reliable, monitorable, and maintainable over time.
• Communicate results, assumptions, and uncertainty clearly, enabling informed decision-making rather than black-box outputs.
• Support the team by sharing knowledge, setting best practices, and acting as a technical sparring partner for other data scientists.