Research Scientist, SAMBA, DeepMind

Digitailor; New York (NY); On-site; USD 207,000 - 300,000; Full time

Job summary

Google DeepMind is seeking a Research Scientist for the SAMBA team in the Responsible Research Group (R2) to study model behaviors and their societal impact. You will design tools and experiments, collaborate with researchers and engineers, and publish results.

The role requires a PhD or equivalent, strong statistical/data-analysis skills, and experience with Python/R and industry codebases. Competitive US salary, 20% bonus target, equity, and benefits.

Qualifications

• PhD in CS, Economics or related field, or equivalent practical experience.
• 5 years in statistics, data analysis and visualization.
• 5 years programming experience with languages like Python or R.
• 2 years experience with AI evaluation.
• 2 years experience with industry codebases.

Responsibilities

• Identify new research areas and questions.
• Design and conduct research and experiments.
• Develop and test new metrics and measures.
• Perform data analysis to synthesize and visualize research findings and evaluation results.
• Lead writing results for research publications.

Skills

Statistical concepts

Data analysis

Programming (Python/R)

AI evaluation

Industry codebases

Education

PhD in CS or Economics

Tools

Pandas

NumPy

Scikit-learn

Job description

As a Research Scientist on the Sociotechnical Analysis of Model Behavior (SAMBA) team in the Responsible Research Group (R2), you will conduct research on model behaviors that impact people and society. You will design tools and methods for measuring the impact of AI on society, broadly defined, design experiments, and develop measures to characterize model properties relevant to responsibility and safety. As one part of your work, you will collaborate closely with other Research Scientists and Research Engineers to build frontier evaluations, apply them in practice, and publish results. You will be joining a specialized Responsibility team within Google. While our reporting structure sits within Google's broader Trust and Safety organization, our work remains deeply integrated with Google 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 diverse 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: $207000 - $300000 (USD) + 20% bonus target + equity + benefits Learn more about benefits at Google .

Minimum Qualifications

PhD in Computer Science, Economics or a related field, or equivalent practical experience. 5 years of experience with statistical concepts, data analysis, and visualization. 5 years of experience with programming languages (e.g., R, Python), relevant libraries (e.g., Pandas, NumPy, Scikit-learn), or other scripting languages. 2 years of experience with AI evaluation. 2 years of experience working with industry codebases.

Preferred Qualifications

Experience creating AI evaluations or benchmarks. Advanced understanding of statistical concepts, and ability to perform data analysis and visualization. Excellent communication and collaboration

Skills

an ability to effectively communicate and work with researchers from a wide variety of backgrounds in research publications, policy briefs, or presentations targeted at both technical and non-technical audiences. Peer reviewed publication on AI auditing/evaluation, especially if it relates to societal impact Responsibilities Identify new research areas and questions. Design and conduct research and experiments. Develop and test new metrics and measures. Perform data analysis to synthesize and visualize research findings and evaluation results. Lead writing results for research publications.