Principal Applied Data Scientist - AI for Good Lab

Overview

The AI for Good Lab is hiring a Principal Applied Data Scientist to join our team in Redmond to design, build, and deliver AI-driven solutions to address complex, interconnected societal challenges. 

Our Lab spans a broad and evolving portfolio, from understanding how AI is diffusing across the world and its economic opportunities, to powering disaster response and resilience, as well as advancing sustainability and cybersecurity. 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 data scientists, researchers, and research organizations, as well as policymakers and practitioners 

You will provide senior technical leadership for applied AI and data science initiatives, defining technical direction for advanced AI systems across humanitarian response, biodiversity, sustainability, public policy, and global development with deep application of data science, cloud platforms, and economics. As a trusted advisor, you will partner with leaders across Microsoft, academia, nonprofits, and government to guide responsible, evidence-based AI solutions to turn insights into impact. 

You bring a strong appetite for learning new domains and technologies, paired with agile decision-making, flexibility in how you work, and a growth mindset. You contribute to a positive, inclusive team culture through clear documentation, ethical research practices, and active knowledge sharing as you navigate complex, evolving challenges.

Our mission is to empower every person and every organization on the planet to achieve more.

Responsibilities

• Lead and develop applied AI solutions (LLMs, Agents, Computer Vision) 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. 

• 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. 

• Rapidly prototype and validate approaches using modeling, statistics and experimentation; select methods under real-world constraints (cost/latency, safety, privacy, maintainability). 

• Design and build reliable, maintainable, end-to-end systems spanning data pipelines, model lifecycle, evaluation/telemetry, deployment, and operations. 

• Advance the AI for Good Lab research agenda by authoring technical papers and presentation, published both internally and externally . 

• Work in close partnership with other researchers and research organizations, as well as policy, industry, and nonprofit stakeholders, to co-create solutions 

• Present findings with clear and compelling narratives, using impactful visualizations and storytelling to articulate insights that drive understanding and action. 

• Lead through influence by shaping technical direction and standards (model evaluation, responsible AI, safety/privacy, and monitoring), aligning collaborators, navigating tradeoffs, and sustaining momentum across teams and institutions. 

Qualifications

Minimum/Required Qualifications:

• Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research)
  • OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics, predictive analytics, research) 
  • OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR equivalent experience. 

Preferred Qualifications:

• Deep foundation in AI, machine learning, statistics, or related quantitative methods applied to real-world proble