About The Position

Are you excited to harness AI and data science to tackle some of the world’s most pressing societal challenges? Would you like your work to meaningfully impact the lives of your family, friends, and communities around the globe? The AI for Good Lab is hiring a Principal Applied AI and Data Scientist to design, build, and deliver AI-driven solutions to complex, high-impact societal problems. Our work spans a broad and evolving portfolio—including powering disaster response and resilience, advancing sustainability, understanding how AI is diffusing across the world and its economic opportunities, and improving digital equity. These challenges are inherently ambiguous and interdisciplinary, demanding creativity, strong research instincts, and the ability to move decisively from uncertainty to insight and action. We are an agile, fast-moving applied research team that uses modern AI as a force multiplier—accelerating discovery, sharpening insight, and driving decisions that matter. We continuously pivot toward where our work can create the greatest impact now. In this role, you will use AI and data science to research and build solutions that inform and drive real-world decisions, working in close partnership with other researchers and research organizations, as well as policymakers and practitioners. You will lead through influence, collaborating across roles, disciplines, and organizations to turn insight into real-world decisions. You bring a strong appetite for learning new areas and technologies, paired with agile decision-making, flexibility in how you work, and a growth mindset that shapes how you approach complex, evolving challenges.

Requirements

  • Bachelor's Degree in Computer Science, Statistics, Economics, Engineering, Social Science, or a related field AND 6+ years of applied experience OR Computer Science, Statistics, Economics, Engineering, Social Science, or a related field AND 4+ years of applied experience OR Doctorate in Computer Science, Statistics, Economics, Engineering, Social Science, or a related field AND 3+ years of applied experience
  • OR equivalent experience.

Nice To Haves

  • Experience in AI, machine learning, statistics, or related quantitative methods applied to real-world problems.
  • Experience working end-to-end with data—from sourcing and exploration through modeling, interpretation, and communication.
  • Proficiency in at least one scientific programming language (Python, R or equivalent languages) and experience with SQL or similar query languages.
  • Experience communicating complex ideas clearly and persuasively to non-technical audiences.
  • Proven ability to influence outcomes and lead work in cross-functional, matrixed environments.
  • Experience collaborating with academic institutions, NGOs, humanitarian organizations, or public sector partners.
  • Familiarity with modern AI techniques used for applied research - such as working with LLMs, embeddings, and AI-assisted analysis of social, economic, or behavioral data.
  • Background or interest in domains such as economics, sustainability, humanitarian response, cybersecurity, public policy, or social impact.
  • Comfort working in fast-changing, impact-driven environments.

Responsibilities

  • Develop applied AI and data science solutions by identifying and gathering data, shaping problem formulations, applying AI, machine learning, and statistical methods, and generating insight with real-world impact.
  • Distill large, ambitious, and highly ambiguous problem spaces—such as AI diffusion and economic opportunity, disaster response and resilience, sustainability, and cybersecurity—into concrete, actionable applied AI and data science work.
  • Use AI creatively as a research and solution-building tool, combining quantitative methods, experimentation, and domain knowledge to surface patterns, test ideas, and inform decisions.
  • Present findings with clear and compelling narratives, using impactful visualizations and storytelling to articulate insights that drive understanding and action.
  • Work in close partnership with other researchers and research organizations, as well as policy, industry, and nonprofit stakeholders, to co-create solutions
  • Lead through influence by shaping direction, aligning collaborators, navigating tradeoffs, and sustaining momentum across teams and institutions.
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