Project Lead, Data Scientist at OECD

THE POSITION The Economics Department is looking for an experienced and creative Project Lead, Data Scientist . The ideal candidate will bring a strong track record in project management and possess broad, in-depth knowledge of the full spectrum of data science solutions including generative AI, machine learning, big data, text mining and natural language processing (NLP). Familiarity with nowcasting, econometric modeling, use of firm-level data, geo-spatial analysis and other applications of data science to economic issues would be considered a further advantage. This role offers a unique opportunity to play a leading role in the newly created IT and data-focused unit within the Policy and Research Branch (PRB) of the Economics Department. The position reports to a Senior Economist. We are looking for someone with a strategic mindset, strong technical expertise, and the leadership skills to drive innovation at the intersection of policy and technology. Main Responsibilities Strategic Data Science Advice and Support • Provide expert guidance on the most innovative and suitable data science solutions to support ECO’s policy research and economic analysis. • Proactively contribute ideas to enhance existing projects by integrating cutting-edge data science tools and methodologies. • Respond to data science requests and inquiries from across the Economics Department. • Deliver training sessions and build internal capacity on data science • Represent the Economics Department (ECO) in meetings and working groups related to data science. • Draft briefing notes and deliver presentations showcasing ECO’s work and experience in the field of data science. • Act as a key liaison with other OECD departments and external organisations on collaborative data science initiatives, particularly in areas such as economic analysis and nowcasting.Project management • Lead data-science projects from inception to delivery • Drafting project blueprints, developing proofs of concept and progress reports • Human resource coordination (e.g. managing consultants, overseeing training) • Technical scoping (e.g. server infrastructure, programming languages) • Budget planning and oversight (e.g. licensing, consultancy costs) • Timeline and milestone management, ensuring on-time delivery.