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Introduction The selected person will join the Technopolis Group Data Science Unit (DSU), whose members work across different country offices. Our growing team brings together diverse academic backgrounds and a shared passion for developing data science applications to improve policymaking. The DSU contributes to policy consulting projects and conducts R&D to develop and test new applications, sometimes in collaboration with internal and external partners. Its work includes record linkage, classification, natural language processing, web scraping, generative AI and dynamic visualisations. As an intern, you will work alongside experienced data scientists and policy consultants, applying and developing your technical skills to address real-world policy questions. About this job The role of the intern in data science for public policy will be to support the data science components of policy evaluations , sectoral studies and strategic consultancy projects. Our clients include French regional councils, the French Development Agency (AFD), ADEME, the European Commission and multilateral development banks. You will be part of the DSU and collaborate with colleagues across policy areas, including science, technology and innovation, economic development, the green transition, international cooperation and health. You may also contribute to internal R&D and business development activities, particularly the preparation of data science approaches for project proposals. No previous professional experience is required. Relevant coursework, academic research and personal coding projects will be considered. We are looking to recruit a full-time intern for at least 6 months starting in Automn 2026 . Internship should be sponsored by the intern’s university (stage conventionné). Your profile We are looking for a curious and motivated individual who enjoys working with data and wants to understand how data science can inform public policy. Suitable candidates should have: Master’s-level studies in data science, computer science, statistics, economics, engineering or another relevant discipline with a strong quantitative component, and be eligible for a university-sponsored internship. Practical programming skills in Python, demonstrated through coursework, research or personal projects, and the ability to write and understand their own analytical code. Good foundations in statistics and quantitative analysis, together with an interest in economics and public policy and in interpreting analytical results in their policy context. Basic familiarity with machine learning or natural language processing, and an interest in using generative AI and large language models programmatically through APIs for data processing, text analysis and knowledge extraction. A careful and structured approach to working with data, including attention to data quality, validation, documentation and reproducibility. An interest in public policy and in using data science to support evidence-based policymaking , particularly in areas such as science, technology and innovation, economic development, the green transition or health policy. Fluency in French and English, good communication skills and an ability to work collaboratively in an international and multicultural environment. A third language would be an asset. Your responsibilities Working under the guidance of experienced colleagues, you will: Support the design and implementation of data science analyses to answer policy questions, writing code in Python. Collect, clean, link and validate data from multiple sources, including open datasets, databases and web-based sources. Help develop and test analytical workflows, potentially involving machine learning, NLP and LLM APIs for classification, text analysis and knowledge extraction. Contribute to indicators, scoreboards and visualisations, including dashboards where relevant, to make findings accessible to different audiences.

Full time paid Internship DSU/ Stage DSU Paris

Don't apply unprepared

Full time paid Internship DSU/ Stage DSU Paris

Don't apply unprepared