Senior Data Scientist
Role details
Job location
Tech stack
Job description
Our Data Science Team works in partnership with experts across the business, applying data science methods to real-world public policy and evaluation challenges. The team delivers applied data science across client projects, while also developing new approaches that combine quantitative analysis, methodological rigour, and the responsible use of emerging technologies such as generative AI. We are looking for a Senior Data Scientist to contribute to the growth and success of the team through strong applied data science delivery, while also helping to build a developing area of work at the intersection of data science, impact evaluation, behavioural insight, and AI-enabled quantitative analysis. The role will involve working with complex, real-world data; contributing to statistical and causal analysis; and supporting the development and testing of AI-supported analytic workflows that reflect good evaluation practice. You will typically work on several projects at a time, collaborating with policy researchers, evaluators, and technical colleagues across the organisation. The role includes contributing to analytical outputs, drafting sections of reports and proposals, and presenting findings to clients and stakeholders. We are particularly interested in candidates with experience in applied analysis who are motivated by using data science to answer complex policy questions. We offer a flexible, hybrid working model, allowing you to balance working from home with use of our Brussels office.
Requirements
A strong quantitative background in data science, statistics, economics, behavioural science, psychology, or a related social science. Professional experience applying data science or quantitative analysis in real-world delivery contexts, such as policy analysis, impact evaluation, consulting, or applied research. Strong applied data science capability, including: working with messy, real-world datasets, exploratory data analysis and feature construction, statistical modelling and inference, and development of reproducible analytical workflows. Proficiency in Python for data analysis. Experience contributing to, or working closely with, impact evaluations or applied causal analysis, with an understanding of counterfactual reasoning and common threats to validity - including: experience with quasiexperimental or causal methods such as differenceindifferences, regressionbased designs, matching, or related approaches; and applied experience drawing on behavioural or social science to inform evaluation design, analysis, or interpretation. Ability to critically assess analytical outputs - including results produced by automated or AI-assisted approaches - and to explain their strengths, limitations, and assumptions clearly. Strong written and verbal communication skills, including the ability to communicate technical and methodological concepts to non-technical audiences. Desirable (but not essential) Experience contributing to the development, testing, or use of AIenabled analytic tools or workflows, including decisionsupport or semiautomated analysis. Experience working in consulting, government, or public sector research environments. Experience contributing to technical sections of reports or proposals for clients.