Applied Data Scientist – Compute & Experimentation

About the position

Are you an experienced Applied Data Scientist (3+ years of experience) excited to use strong technical and analytical skills to power our mission to bring the benefits of AI to the world? Join Google DeepMind’s Core Analytics Team! Working closely with our Generative AI/Gemini org, you will bring a data lens to strategic business problems around compute and infrastructure strategy, directly enabling our frontier research and product development efforts. This role focuses on leveraging data science techniques – particularly advanced SQL, Python for analysis, and statistical methods – to drive strategic decisions and generate insights, rather than deep machine learning model development.

Responsibilities

• Work directly with stakeholders, including senior leaders, to identify, scope, and prioritise high-impact analytical questions related to compute and infrastructure strategy.
• Conduct rigorous, end-to-end analyses using SQL, Python, and statistical methods to uncover insights, model trends, and answer complex questions about efficiency, usage patterns, and strategic investments.
• Translate complex analytical findings into clear, compelling narratives and actionable recommendations for diverse audiences (technical and non-technical) through presentations, reports, and dashboards.
• Develop and maintain tools (dashboards, reports) to provide ongoing visibility into key compute metrics and empower stakeholders with self-service analytics where appropriate.
• Collaborate with engineering and product teams to highlight data gaps and advocate for the collection of telemetry needed to improve future analyses and decision-making.
• Share knowledge, contribute to the team's analytical roadmap, and help improve our overall processes and best practices.

Requirements

• 3+ years of experience as a Data Scientist, Data Analyst, Quantitative Analyst, or Product Data Scientist.
• Proven ability to understand ambiguous problems, formulate key questions, and design/execute appropriate analytical approaches.
• High proficiency in using SQL to extract, manipulate, aggregate, and analyze complex datasets from various sources.
• Strong track record of building relationships, collaborating effectively, and presenting complex findings and recommendations clearly and persuasively to diverse audiences, including senior leadership.
• Solid understanding and practical application of statistical concepts for analysis (e.g., hypothesis testing, regression, forecasting).
• Ability to manage multiple analytical projects simultaneously, prioritise effectively, and deliver high-quality insights in a dynamic environment.

Nice-to-haves

• Experience with or a strong interest in cloud compute metrics, large-scale infrastructure, hardware accelerators (GPUs/TPUs), or related technical domains.
• Proficiency in Python and common data analysis libraries (e.g., Pandas, NumPy, SciPy, Scikit-learn, Matplotlib/Seaborn).
• Experience creating effective dashboards and visualizations using tools like Tableau, Looker, Google Data Studio, or similar.
• Experience designing and implementing ELT workflows (using tools like dagster, dbt).
• Experience mentoring others in analytical techniques or tools.

Benefits

• Direct Strategic Impact: Your analysis and recommendations will directly inform critical decisions about Google DeepMind's compute resources and infrastructure investments.
• Deep Domain Expertise: Opportunity to become a subject matter expert in the rapidly evolving and critical domain of AI compute and infrastructure.
• Leadership Exposure: Work closely with senior leaders and key decision-makers, honing your communication and influencing skills.
• Collaborative Environment: Be part of a supportive and highly skilled data & analytics group, learning from peers and contributing to a culture of analytical excellence.