Senior Manager / Assistant Director, Psychological Research & Evaluation

About the role

The Strategy, International & Research (SIR) Directorate drives MSF's strategic planning, international engagement and research and analytics. Within it, the Psychological Research & Evaluation (PRE) team applies psychological and social research, evaluation and advanced analytics to support policymaking and service delivery. As Senior Manager/Assistant Director you will design and run rigorous research and advanced data analytics to answer complex social and policy questions, using statistical methods, machine learning and emerging AI technologies.

Key responsibilities

• Design and conduct quantitative research and advanced analytics to generate actionable insights for policymakers and service providers.
• Apply techniques such as longitudinal analysis, predictive modelling, machine learning and causal inference to understand social and family outcomes.
• Use AI tools, including Large Language Models and Natural Language Processing, to analyse structured and unstructured data.
• Identify emerging social trends, evolving needs and potential risks across population groups.
• Develop, validate and test new analytical methods, models and tools.
• Turn complex findings into clear recommendations for policymakers and operational stakeholders.
• Manage research and analytics projects, including methodological design, model validation, deliverables and timelines, and work with internal and external partners.

Required profile

• Degree in Psychology, Statistics, Data Science, Computer Science, Economics, Social Sciences or a related field.
• Strong training in quantitative research methods, statistics or data analytics, with 5 to 7 years of relevant experience.
• Ability to develop, evaluate and validate analytical models and AI-enabled solutions, with a sound grasp of methodological rigour.
• Experience in applied social research, programme evaluation or social policy research is an advantage.

Required skills

• Strong programming and statistical analysis, particularly Python and/or R.
• Multivariate statistical modelling, longitudinal analysis, predictive analytics, machine learning and causal inference.
• AI and ML techniques such as LLMs and NLP.
• Good communication, stakeholder engagement and project management skills.