Stage PFE Data Science – Master ou Ingénierie

We are seeking a motivated Master's or engineering student in their final year of study (end-of-studies internship) to join our data science team to deliver personalized content experiences to healthcare professionals. As a Data Science Intern, you'll work on production machine learning systems that directly impact how medical professionals discover and engage with critical healthcare information.

You'll be embedded in a small, high-impact team responsible for maintaining and improving two core ML models (content recommendation and churn prediction) and/or an optimization system that maximizes business value. This is a hands‑on role where you'll contribute to real‑world systems while gaining experience across the full machine learning lifecycle.

• Feature Engineering & Data Wrangling:
  Design and implement features from healthcare engagement data, working primarily with Pandas and Polars to transform raw data into model-ready datasets
• Model Development:
  Contribute to our existing scikit‑learn and Factorization Machine models, and help prototype our next-generation deep learning architecture
• Optimization Modeling:
  Support our pyomo-based optimization framework that balances recommendation quality with business objectives
• Data Pipeline Development:
  Write efficient SQL queries against our Redshift data warehouse and manage datasets on S3
• Experimentation & Analysis:
  Design A/B tests, analyze model performance, and communicate findings to stakeholders

• Currently pursuing a Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or related quantitative field
• Strong Python programming skills with experience in data manipulation and analysis
• Solid understanding of machine learning fundamentals (supervised learning, model evaluation, feature engineering)
• Proficiency with Pandas for data wrangling
• Working knowledge of SQL for data extraction and transformation
• Familiarity with scikit‑learn or similar ML libraries
• Strong problem‑solving skills and attention to data quality
• Ability to work independently and communicate technical concepts clearly

• Any of the following is a plus, not a requirement for application:
• Experience with Polars or other high-performance data processing libraries
• Exposure to recommendation systems or churn prediction models
• Knowledge of optimization modeling (linear programming, constraint optimization)
• Experience with pyomo or similar optimization frameworks
• Understanding of deep learning frameworks (PyTorch, Tensor Flow)
• Experience working with cloud data warehouses (Redshift, Snowflake, Big Query)
• Knowledge of AWS services, particularly S3
• Background or interest in healthcare/medical domains

• End-to-end ML system development in a production environment
• Advanced feature engineering techniques for recommendation and churn prediction
• Optimization modeling and balancing multiple business objectives
• Working with large-scale healthcare data
• Best practices in ML model deployment and monitoring
• Cross-functional collaboration with product and business teams