Job descriptionIn this role, you will apply advanced quantitative methods and behavioral science to understand the human drivers behind global health outcomes. You will work with complex, real-world datasets to generate insights that inform how healthcare is delivered and improved in low- and middle-income countries. The role combines rigorous analytical research with the ability to translate findings into clear, decision-relevant insights for global health stakeholders. Key Responsibilities Design and execute advanced statistical analyses to uncover behavioral and systemic drivers within global health datasets. Apply quantitative methods, including statistical modeling and machine learning approaches, to generate robust and actionable insights. Work with large, real-world datasets and contribute to the development and management of analytical workflows and data pipelines. Collaborate closely with Product, AI, and research teams to translate analytical findings into scalable data-driven tools and solutions. Interpret complex analytical results and communicate clear implications, recommendations, and so what insights for internal teams and external partners. Contribute to the design of research studies and data collection approaches, ensuring analytical rigor across the research lifecycle. Produce high-quality reports, visualizations, and presentations for global health decision-makers. Qualifications & Requirements 5–6+ years of experience in quantitative research, applied analytics, or data-focused research roles, ideally within global health, development, or LMIC contexts. Strong hands-on expertise in R programming , with demonstrated experience building or contributing to shared codebases in professional settings; ability to work independently with complex, real-world datasets from day one. Python experience is an added advantage. Solid applied statistics and quantitative research foundation, including direct experience with data cleaning, QA, regression analysis, study design, and visualization of large or messy datasets. Experience applying analytical methods to both structured and unstructured datasets, including exposure to Natural Language Processing (NLP) or text-based data analysis, is an added advantage. Proven experience working with behavioral or health outcomes data, particularly in global health/public health settings, rather than purely policy, strategy, or consulting-led roles. Strong analytical interpretation skills, with the ability to synthesize findings into structured, stakeholder-friendly insights and actionable recommendations for non-technical audiences. Demonstrated experience contributing to scientific publications, white papers, or research reports, reflecting strong written communication and evidence-based documentation skills. Advanced degree in Public Health, Economics, Statistics, Neuroscience, or another related quantitative discipline; PhD preferred but not mandatory. Experience with platforms such as Databricks is a plus. Excellent written and verbal communication skills; consulting-style communication and fluency in French language are considered strong advantages. Must be based in New Delhi (or open to relocation), with willingness to travel up to 10% domestically and internationally.
