Senior Strategist, Data & AI (Remote - US, UK, Nigeria, Ethiopia, India or Rwanda)

Resolve to Save Lives (RTSL) is a global health organization that partners locally and globally to create and scale solutions to the world’s deadliest health threats.

Millions of people die from preventable health threats.

We collaborate to close the gap between proven, life-saving solutions and the people who need them.

Since 2017, we’ve worked with governments and other partners in more than 60 countries to save millions of lives.

We work toward a future where people live longer, healthier lives, communities flourish, and economies thrive.

This is an ambitious vision, and it inspires us and our partners to make progress every day.

Position Purpose: The Senior Strategist, Data & AI strengthens the capacity of RTSL and its government partners to use data, digital systems, and artificial intelligence to improve public health programs and decision-making.

Working across RTSL's program portfolio, the role brings together public health strategy, data architecture, digital transformation, and AI governance to identify high-value opportunities and help translate them into practical, sustainable approaches.

The Senior Strategist advises program and country teams on data architecture, interoperability, data governance, and AI readiness; shapes and prioritizes data- and AI-enabled initiatives; and builds RTSL's capacity to use emerging technologies responsibly and effectively.

Externally, the role works with governments, technical partners, and the broader global health ecosystem to advance country-owned approaches to stronger data systems and responsible AI.

Success in the role means that RTSL and its partners are making better-informed decisions about where and how to invest in data and AI, with stronger underlying data systems, clearer standards and safeguards, and practical applications that deliver measurable public health value.

Core Duties and Responsibilities: Data Strategy and Architecture Advise RTSL program and country teams and government partners on strengthening the data foundations needed for effective public health programs, including data architecture, quality, interoperability, metadata, governance, accessibility, and appropriate data use.

Ensure teams understand how data flows across systems and identify fragmentation, duplication, quality issues, and other barriers to effective program management and decision-making.

Support governments and partners in developing practical, sustainable approaches to data architecture and interoperability that strengthen existing systems and promote country ownership.

Translate public health and program needs into clear data requirements and help bridge communication among public health, epidemiology, product, data, and technology teams.

Ensure high standards for data quality, usability, interoperability, governance, privacy, and sustainability in collaboration with IT, Legal, and relevant technical teams.

Track developments in health information architecture, interoperability standards, digital public goods, analytics, and related fields and assess their implications for RTSL's programs and country partnerships.

Applied AI, Innovation, and Responsible Use Shape RTSL's approach to the responsible programmatic use of AI and advanced analytics, ensuring that investments are driven by public health problems and measurable value rather than technology alone.

Identify and prioritize high-value opportunities where AI could improve planning, implementation, clinical or public health decision support, analysis, monitoring, or learning -- in close collaboration with program, country, and digital teams.

Guide structured assessment of proposed AI use cases, considering the problem to be solved, user and workflow needs, data readiness, feasibility, public health value, equity, privacy, safety, sustainability, and country context.

Advise teams on whether to build, buy, adapt, or partner for data- and AI-enabled solutions, emphasizing reuse, interoperability, sustainability, and fit for purpose.

Partner with organizational leadership, IT, and Legal to translate RTSL's AI policies and principles into practical guidance and appropriate review processes for programmatic applications.

Promote responsible AI practices, including appropriate human oversight, transparency, accountability, privacy, equity, and mechanisms for identifying and responding to risks.

Lead responsible experimentation and learning, helping RTSL distinguish promising innovations from approaches that are not sufficiently useful, feasible, or sustainable to pursue.

Program Advisory and Organizational Capability Serve as a senior resource to RTSL's program and country teams, helping them integrate data and AI considerations into program design, implementation, monitoring, and scale.

Develop practical frameworks, decision aids, guidance, and tools that enable teams to assess data and AI opportunities consistently and rigorously.

Build organizational capability in AI and advanced tools through training, coaching, communities of practice, and practical learning opportunities.

Help teams develop sufficient AI and data literacy to engage effectively with technical experts, vendors, government counterparts, and partners and make informed decisions.

Provide strategic input to digital product and innovation initiatives where broader questions of data architecture, interoperability, AI, or cross-program applicability are relevant, while leaving product ownership and delivery with the responsible technology teams.

Capture and share learning from data, digital, and AI initiatives across programs and countries, ensuring that evidence, successes, and failures inform future strategy, investment, and implementation.

External Advisory, Partnerships, and Cross-Functional Collaboration Advise government and public health partners on data architecture, interoperability, governance, organizational readiness, and responsible AI adoption in primary health care, epidemic preparedness, and other areas relev