Stage Innovation : Ingénieur Data Science / Intelligence Artificielle
Core
Develop a multi-source data analysis system to detect early warning signals and anomalies in public health, pharmacovigilance, and sanitary security domains.
Role type
Intern Data Scientist / AI Engineer (Signal Detection)
Builds
Automated alerting systems for critical event detection
Domain
Public health, pharmacovigilance, sanitary security
Deliverable
production ML models
Required skills
Anomaly detection, clustering, predictive modeling, NLP (NER, topic modeling, document classification), Python (Pandas, Scikit-learn, PyTorch/TensorFlow), data visualization (Plotly, Dash, Streamlit)
Preferred skills
Experience with heterogeneous or multi-source data (text, time series, events)
Technologies
Python, Pandas, Scikit-learn, PyTorch, TensorFlow, Plotly, Dash, Streamlit, BeautifulSoup, spaCy
Responsibilities
Identify anomalies indicating risks or critical events, define rules or models to qualify signals as relevant/urgent, analyze structured and unstructured data from multiple sources
Seniority
Intern (final year engineering school or Master's student)
