Research Assistant [Evaluation Officer]

The Policy Institute at King’s College London works to solve society’s challenges with evidence and expertise. As part of the Faculty of Social Science and Public Policy, we combine the rigour of academia with the agility of a consultancy and the connectedness of a think tank. This role sits within the Evidence Development and Incubation Team (EDIT), a specialist evaluation team within the Policy Institute. EDIT partners with government departments, public bodies, charities and other organisations to understand the impact of their work.

Our activities include:

• Designing and delivering impact evaluations to assess the impacts of interventions on key outcomes, using experimental and quasi-experimental approaches
• Conducting implementation and process evaluations to explore how interventions operate in practice and how they are experienced by participants
• Supporting organisations to develop robust internal evaluation strategies, including the systems, skills and processes needed to embed evaluation in their work.

Beyond individual projects, EDIT advocates for the use of evidence in policy and practice, and works closely with members of the What Works Network to strengthen the wider evaluation ecosystem and promote the adoption of evidence-based interventions.

About the role: The Research Assistant (Evaluation Officer) will support EDIT in delivering ongoing and new evaluation and research projects. Current work includes evaluations of programmes across primary, secondary, and further education; interventions aimed at reducing homelessness; and initiatives supporting young people to progress into employment. The role has a strong focus on quantitative evaluation methods. The ideal candidate will have formal training in quantitative research methods (for instance statistics, econometrics, or similar subjects) – using R – and experience applying these skills in practice on evaluation and research projects. We are particularly interested in candidates with experience working on commissioned research within a research organisation, consultancy, or academic setting. We also welcome applicants who bring subject-matter expertise from working in relevant policy areas, such as education, employment, youth violence reduction, homelessness, or related fields.

The successful candidate will be highly organised, analytically rigorous, comfortable working collaboratively across multiple projects, and able to contribute flexibly within a fast‑paced research environment. This is a full‑time post (35 hours per week), and you will be offered a two‑year fixed‑term contract. Research staff at King’s are entitled to at least 10 days per year (pro‑rata) for professional development.

About you: To be successful in this role, we are looking for candidates to have the following skills and experience:

• Formal training in quantitative research methods (e.g., statistics, econometrics, or similar disciplines).
• Training in, and practical experience using R statistical software for data analysis.
• Experience cleaning, managing, and analysing large or complex datasets; producing clear and well‑documented code; and developing analysis plans.
• Training in, and understanding of, evaluation methods, including experimental and quasi‑experimental approaches (e.g., RCTs, difference‑in‑differences, regression discontinuity, propensity score matching).
• Practical experience applying quantitative research methods to evaluation or research projects, for instance in education, employment, homelessness, or other relevant policy areas.
• Excellent organisational and time‑management skills, with a high level of attention to detail.
• Strong written and verbal communication skills.
• Ability to work collaboratively and effectively as part of a project team.
• Experience working on commissioned research or consultancy‑style projects.
• Experience of designing survey studies and/or of analysing survey data.
• A degree in a relevant subject, such as economics, social policy, political science, statistics, data science, quantitative social science, or a related discipline.
• Experience using causal inference techniques in applied evaluation or research settings.

We ask all candidates to submit a copy of their CV, and a supporting statement, detailing how they meet the essential criteria listed in the person specification section of the job description.