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.