Caisse nationale de solidarité pour l'autonomie

About the Company

La CNSA est à la fois une caisse, une agence et un espace public d’échanges pour l’autonomie des personnes âgées et des personnes handicapées. La CNSA gère la branche Autonomie de la Sécurité sociale. La branche Autonomie a pour mission de sécuriser le financement des aides à l’autonomie et garantir l'équité territoriale pour répondre aux besoins des personnes âgées, des personnes en situation de handicap et de leurs aidants.

Listed Jobs

Company Name

Caisse nationale de solidarité pour l'autonomie

Job Title

STAGE - Appui au pilotage et à la structuration de l’offre de services métier pour les territoires

Job Description

Job title: Internship – Support in the Management and Structuring of Service Offerings for Territories Role Summary An internship focused on data‑driven analysis to strengthen territorial service provision for persons with disabilities and the elderly. The intern will support the identification of priority territories, analyze care pathways, assess service quality, and enhance data reliability in the Information Systems of the MDPH (Maison Départementale des Personnes Handicapées). Expectations - Complete a 6‑month or longer internship. - Contribute to data analytics projects, deliver actionable insights, and support the strategy team in improving service delivery. - Work collaboratively with data engineers, statisticians, and MDPH stakeholders. Key Responsibilities 1. Identify territories requiring stronger support using multivariate data analyses (activity data, outcome indicators, IT deployment metrics). 2. Analyze care pathways (education, employment) for people with disabilities to support the MDPH strategy team. 3. Conduct analyses of specific surveys and collect open‑data sources. 4. Evaluate service quality metrics, including data mining of social media and classification techniques, and assess resource‑activity balance for MDPH. 5. Perform data integrity checks on data warehouses (MDPH SI, orientation tracking SI) to detect anomalies before data ingestion. 6. Develop decision trees from MDPH SI data and define rules to populate a suggestion engine for MDPH evaluators. Required Skills - Multivariate data analysis. - Proficiency in R, Python, and SQL. - Knowledge of data mining techniques for anomaly detection. - Ability to work with structured and semi‑structured data, open data integration, and classification methods. Required Education & Certifications - Current enrollment in a master’s program or engineering school with a specialization in data engineering or data science. - No specific certifications required beyond academic coursework. ---

Paris, France

Hybrid

13-03-2026