Manager, AI – Diagnostics

Clinton Health Access Initiative, Inc.

AI diagnostics research manager guiding CHAI’s global health investments in machine-learning diagnostic tools. Assessing evidence, readiness, costs, and impact for low- and middle-income countries.

Posted 8/11/2026full-timeRemote • 🇺🇸 United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates strong quantitative skills and expertise in machine learning concepts, with the ability to assess data quality and model performance. Proficient in developing analytical tools and workflows using modern AI technologies while effectively communicating complex information to diverse stakeholders.

Highest-signal resume keywords

Quantitative AnalysisMachine Learning ConceptsAI Tools PrototypingData Science ProficiencyStakeholder Engagement

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ScienceStatisticsBiostatisticsEpidemiologyMachine LearningPythonRData AnalysisModel ValidationCost-Effectiveness Analysis

Soft Skills

Problem-SolvingAnalytical SkillsCommunication SkillsCollaborationEntrepreneurial Mindset

Tools & Technologies

ClaudeChatGPTGeminiMicrosoft OfficeAI Automation Tools

Industry Keywords

Global HealthPublic HealthDigital HealthHealth DataLow- and Middle-Income Countries

Tech Stack

Tools & technologies

ChaiPython

About the role

Key responsibilities & impact

Lead research on the AI diagnostics landscape, assessing current and emerging tools and their relevance for low- and middle-income countries
Assess technical readiness of priority diagnostics, including training datasets, model architectures, sample sizes, and validation
Use disease-burden data to identify high-burden conditions lacking viable AI diagnostics
Develop and maintain market intelligence covering evidence, performance, cost, and regulatory status
Lead maturity assessments from proof-of-concept through regulatory approval and deployable scale
Prepare analyses, briefs, presentations, technical documentation, and recommendations for leadership, government partners, and donors
Build and maintain analytical tools and workflows using modern AI tools to automate research and reporting
Support engagement with technology developers, research institutions, and partners on data and model questions
Support cost-effectiveness prioritization and 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 requested by the team lead or senior leadership

Requirements

What you’ll need

Bachelor's degree or equivalent and 4 to 8 years of relevant professional experience
Quantitative background in data science, statistics, biostatistics, epidemiology, economics, computer science, mathematics, or a related field
Strong quantitative skills and command of core machine learning concepts
Ability to assess training-data quality and representativeness, model performance and architectures, sample sizes, and validation
Excellent problem-solving and analytical skills
Ability to synthesize complex technical and quantitative information for non-technical audiences
Familiarity with modern AI tools and platforms such as Claude, ChatGPT, and Gemini
Willingness to use modern AI coding tools to prototype, automate, and build analytical tools
Entrepreneurial mindset and comfort in a fast-paced, evolving environment
Ability to work independently with limited guidance, navigate ambiguity, and implement new approaches
Strong written and oral communication skills in English
Ability to build collaborative relationships with diverse stakeholders
High proficiency in Microsoft Office
Willingness and ability to travel internationally 20–40% of the time, including occasional multi-week trips
Preferred: Graduate degree in a quantitative or health-related field
Preferred: Proficiency in Python, R, or other programming languages and data-analysis or machine-learning workflows
Preferred: Familiarity with large datasets, including IHME, WHO, and other public data sources
Preferred: Hands-on experience with AI “vibe-coding” and automation tools
Preferred: Experience working with governments, multilateral organizations, and/or in LMIC settings
Preferred: Background in global health, public health, digital health, or applied research using health data
Preferred: Proficiency in languages spoken in CHAI program countries

Benefits

Comp & perks

Telecommute / flexible remote location
20–40% international travel, including occasional multi-week trips
Equal employment opportunity environment
Diversity and inclusion commitment