Data Scientist

Role summary We are seeking skilled and motivated Data Scientists to join our team in Paris. You will work at the intersection of product, research, and engineering. You will analyze user behavior, optimize product performance, and design data-driven features that enhance our AI product suite. This role is ideal for someone who thrives in a dynamic environment, enjoys tackling ambiguous problems, and wants to influence our product roadmap directly. The ideal candidate will have a strong background in data analysis, statistical modeling and machine learning, with a proven track record of delivering high-quality results in a fast-paced environment. If you’re passionate about data, curious about AI, and eager to shape the data science strategy and make an impact, this is the role for you. What you will do • Define key metrics, understand in-depth the performance of our AI products, and identify opportunities for improvement. • Design and analyze experiments (A/B tests, causal inference) to validate hypotheses and guide product decisions. • Design and implement end-to-end data science projects, from data collection and preprocessing to model building, evaluation, and deployment. • Evaluate model performance in training and production, identifying edge cases, and develop frameworks to measure user satisfaction. • Work with engineering to ensure data quality and accessibility for analytics and ML. • Depending on seniority, mentor peers and share best practices in data science and analytics. About you Must-have: • Minimum of 2 years of industry experience as a Data Scientist. • Master's or Ph.D. degree in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field. • Proficiency in Python as well as SQL. • Highly technical but with a strong product acumen. • Experience in extracting insights from large and complex data, summarizing findings and sharing takeaways for product and engineering teams. • Strong statistical intuition and experience with experimental design, causal inference and machine learning algorithms. • Excellent communication and ability to explain complex technical concepts to non-technical audiences. • Creative, curious, and innovative—you love exploring new ways to use data. • Low-ego and a team player, eager to collaborate across functions. Nice-to-have: • Familiarity with DBT or similar tools. • We are looking for folks to work on customer facing products, enterprise products and with the science team, so experience working on one or more related topics is a plus. Hiring process • Recruiter's screening - 35 mins • Hiring Manager's screening - 30 mins • Technical interview - Python + Stats/ML knowledge - 60 mins • Take home + review - 1 week (5 hours) + 60 mins • Value talk interview - 30 mins • Reference checks