This role is a unique opportunity to apply advanced epidemiological and quantitative analytics to high-impact health interventions in some of the world's most challenging contexts. You will have the chance to work across CHAI's diverse health programs, contribute to complex analytical work, and directly influence how resources are allocated to save lives at scale.

This role is open to candidates based in any CHAI program country, pending leadership approval and appropriate work authorization. Candidates should be able to accommodate overlapping working hours with US Eastern Time (ET) to facilitate team collaboration.

Responsibilities

Analytics and modelling

• Apply quantitative and geospatial methods to support CHAI country teams in identifying high-priority programs, geographic targeting opportunities, and health system efficiencies
• Support creation of cost-effectiveness models to enable evidence-based program decision-making to achieve maximal impact
• Appropriately utilize large-scale datasets (e.g., GBD, DHS, national surveys, IHME datasets, implementation cost data) to inform program design and prioritization decisions
• Collaborate across CHAI's disease and geographic programs to gather inputs, validate analytical assumptions, and ensure models reflect on-the-ground program realities
• Support CHAI's engagement with major funders by preparing evidence-based materials that inform prioritization decisions and funding conversations

Evidence-based program development and technical leadership

• Support the design and implementation of new pilot programs, leveraging existing evidence and data to ensure interventions are both impactful and cost-effective
• Conduct rigorous pressure-tests of program theories of change, including critical review of evidence, interrogation of key assumptions, and assessment of causal pathways and counterfactual scenarios
• Collaborate with CHAI country teams and government partners to ensure feasibility and alignment of interventions within national health systems

Qualifications

Education and experience

• Postgraduate degree in epidemiology, economics, or related quantitative discipline
• 3+ years of experience applying quantitative methods to global health or development challenges, including cost-effectiveness analysis, impact evaluations, and mathematical modeling

Technical

• Exceptional analytical and critical thinking skills, with proven capacity to pressure test complex theories of change
• Excellent skills in data management and statistical analysis, including use of software such as Stata, R, or SAS
• Experience in cost-effectiveness modeling and evaluation design (including causal inference using observational data), tailoring methodologies to diverse contexts to generate actionable insights
• Experience assessing and reconciling data quality issues across large survey and administrative datasets, particularly in multi-country settings
• Strong understanding of the LMIC health systems context, including data limitations, operational constraints, and the role of government and partner ecosystems

Operational

• Strong communication skills, including the ability to present complex quantitative findings to donors, government stakeholders, and other diverse audiences
• Demonstrated fluency in using AI tools to synthesize information and produce high-quality analytical outputs, paired with the judgment to critically evaluate AI-generated work, identifying where it falls short or gets things wrong, and applying sound human reasoning to correct, refine, and strengthen the final product
• Proven ability to work independently in a fast-paced environment
• Commitment to collaborative work with a remote, geographically dispersed team across multiple time zones
• Fluency in English

Preferred

• Experience using geospatial methods to support budget optimization, program targeting, or subnational prioritization analyses is an advantage
• Proficiency in one or more languages spoken in CHAI countries

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Originally posted on Himalayas