Data Scientist, Research, DeepMind

Artificial intelligence will be one of humanity’s most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.

We are pushing the boundaries across multiple domains. Our global teams offer learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $232000 - $252000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Minimum qualifications:

• Master's degree in Organizational Behavior, Management Science, Behavioral Science, Human-Computer Interaction, Computational Social Science, or equivalent practical experience.
• 4 years of experience designing and executing multi-method research (e.g., RCTs, field studies, quasi-experiments) to measure cognitive, behavioral, and organizational outcomes.
  
• 2 years of experience researching the impact of AI, collective intelligence, or technological transformation on organizations.

Preferred qualifications:

• PhD degree in Organizational Behavior, Management Science, Behavioral Science, Human-Computer Interaction, Computational Social Science, or equivalent practical experience
• Experience partnering with product/engineering teams to develop science-backed tools or interventions.
• Track record of collaborations with cross-functional leadership in research and product areas.
• Demonstrated ability to translate complex empirical findings into actionable strategies for executive leadership and engineering teams.

Responsibilities:

• Design and execute a portfolio of multi-method research projects spanning generative, experiential, computational, and experimental methodologies, balancing scientific excellence with the pace of a frontier AI lab.
• Define and uphold the team's experimental governance and scientific quality standards, including research ethics, data privacy, and reproducibility protocols.
• Drive research that closes the loop between empirical insights and AI capability development, ensuring behavioral findings directly inform the design and evaluation of new tools, simulations, and benchmarks.
• Collaborate across DeepMind technical teams — and, where relevant, with leading external academic partners — to manage open questions at the intersection of AI and organization science.
• Co-author high-impact research papers, white papers, and executive syntheses that combine scientific authority with broad organizational relevance.