Manager, AI - Diagnostics

Role Description

CHAI is seeking a quantitatively strong researcher to anchor the research and analytics that guide where the AI Diagnostics team invests. Reporting to the AI Diagnostics lead, the individual will help decide which diagnostics carry the greatest impact, judge the data and models behind them, and maintain the evidence base the wider team and its partners rely on. This is a new role with significant independence and the scope to take on greater responsibility and leadership as the team and its portfolio grow. The ideal candidate is analytically rigorous, comfortable with the fundamentals of machine learning, and able to turn a fast-moving and often ambiguous landscape into clear, defensible recommendations. This position is flexible to being based in the United States or in a CHAI program country (subject to country leadership approval and ability to obtain work authorization), and requires 20-40% international travel, including occasional multi-week trips. This position can be levelled at a Manager or Senior Manager depending on level of experience.

Responsibilities

• Lead the team's ongoing research on the AI diagnostics landscape: scanning, assessing, and synthesizing both the tools available today and the promising tools still emerging or yet to be built, and how relevant each is for low- and middle-income countries.
• Assess the technical readiness of priority diagnostics, including the quality and representativeness of training datasets, model architectures, and the adequacy of sample sizes; run focused deep-dive research on priority questions, such as data gaps for specific tools or hardware.
• Use disease-burden data to identify high-burden conditions that lack a viable AI diagnostic, informing CHAI's investment priorities and engagement with developers.
• Develop and maintain CHAI's market intelligence on the AI diagnostics landscape, covering evidence, performance, cost, and regulatory status, as a resource for internal teams and, over time, external partners.
• Lead the maturity assessment of priority diagnostics, from research proof-of-concept through regulatory approval to deployable scale.
• Prepare analyses, briefs, and presentations that communicate strategy, progress, and impact to internal leadership, government partners, and donors.
• Build and maintain analytical tools and workflows, including with modern AI tools, to automate research and reporting.
• Support engagement with technology developers, research institutions, and partners on data and model questions.
• Support the cost-effectiveness prioritization that helps determine where CHAI focuses, and help keep it current as the field evolves.
• Contribute to fundraising and donor engagement, including proposal development and reporting.
• Travel internationally 20-40% of the time, including occasional multi-week trips.
• Undertake other responsibilities as needed at the request of the team lead or senior leadership.

Qualifications

• Bachelor's degree or equivalent and 4 to 8 years of relevant professional experience; backgrounds in quantitative fields such as data science, statistics, biostatistics, epidemiology, economics, computer science, or mathematics are welcome.
• A strong quantitative skill set and a solid command of core machine learning concepts, with the ability to judge training-data quality and representativeness, reason about model performance and architectures, and interpret sample-size and validation questions.
• Excellent problem-solving and analytical skills, with the judgment to deliver a clear, defensible recommendation under time pressure.
• Demonstrated ability to synthesize complex technical and quantitative information for non-technical audiences.
• Familiarity with modern AI tools and platforms (e.g., Claude, ChatGPT, Gemini) with informed perspectives on their relative strengths and limitations.
• Willingness to use modern AI coding tools to rapidly prototype, automate, and build lightweight analytical tools.
• Entrepreneurial mindset and comfort in a fast-paced, rapidly evolving environment, including the ability to work independently with limited guidance, navigate ambiguity, and propose and implement new approaches.
• Strong written and oral communication skills in English, including the ability to prepare compelling presentations, memos, and technical documentation.
• Ability to build collaborative relationships with diverse stakeholders, including government officials, technical teams, and international partners.
• High level of proficiency in Microsoft Office.

Preferred Qualifications

• Graduate degree in a quantitative or health-related field (e.g., data science, machine learning, biostatistics, epidemiology, economics, or public health with a quantitative focus).
• Proficiency in Python, R, or other programming languages, and experience with data-analysis or machine-learning workflows.
• Familiarity working with large datasets, including from IHME, WHO, and other public data sources.
• Hands-on experience with AI “vibe-coding” and automation tools.
• Experience working with governments, multilateral organizations, and/or in LMIC settings.
• Background in global health, public health, digital health, or applied research using health data.
• Proficiency in languages spoken in CHAI program countries (Hindi, French, Swahili, etc.).