Senior Data Scientist - Ecommerce - Freelance

Daily rate: 550

Context

We are looking for a Senior Data Scientist to join the Digital Analytics team within Ecommerce. The Digital Analytics team enables data-informed decision-making across Decathlon ecommerce, driving faster and smarter outcomes. We go beyond descriptive analytics by combining advanced analytics, experimentation, and data science to both understand and shape customer behavior. By embedding these capabilities into our digital products, we power intelligent features, personalization, and continuous optimization at scale. By integrating data across the full product lifecycle, we ensure every feature and iteration delivers meaningful value for both users and the business.

As a Senior Data Scientist, you will play a key role in exploring data, generating insights, and building data-powered product experiences. You will partner closely with product managers, engineers, and analysts to apply predictive and prescriptive analytics, and develop models that directly impact customer experience and business performance. This is a highly product-oriented role: we are looking for someone who combines strong analytical thinking with applied data science, and who has hands-on experience delivering solutions in real-world product environments. You should be comfortable moving from exploration and hypothesis generation to modeling and impact measurement, with a focus on delivering tangible outcomes in a product environment.

Missions

• Build data science & advanced analytics solutions: develop machine learning models and apply predictive and prescriptive analytics to solve complex ecommerce and customer experience problems.
• Own end-to-end use cases: translate business and product requirements into clear data science approaches. Take full ownership from problem discovery to modeling, deployment, and ongoing refinement.
• Continuously monitor and optimize models and analytics solutions to ensure they remain accurate, relevant, and impactful for users and the business.
• Explore & identify opportunities: proactively analyze data to uncover customer behaviors, trends, and high-impact opportunities.
• Collaborate to deliver in production: partner closely with product and engineering to bring solutions live, ensuring scalability, reliability, and business impact.

Tools & Environment

• Databricks, Spark / PySpark, SQL, Python
• TensorFlow / PyTorch
• Jupyter notebooks
• Statsig, Amplitude, Tableau
• Git, MLflow

Working Conditions

No specific details provided.