Research Scientist

In 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.