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Senior Manager, Business Data & Analytics

Deepmind

London, UK Hybrid permanent

Posted: January 12, 2026

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Job Description

Snapshot

The Core Analytics Team (CAT) is tasked with organising and modeling GDM’s data to guide operations and strategy (covering areas like research, compute, people, and product analytics).

CAT is part of our broader Technical Operations and Analytics (TOA) team. Technical Operations and Analytics’s mission is to accelerate GDM’s mission by building the systems, processes, and technology to support data-led decisions and deliver AI to the organization. We are responsible for delivering AI across GDM’s infrastructure to power operations at scale, ensuring we function as a fully 'AI First' organisation.

As we transition to an AI-first organisation, we are seeking a visionary data leader to champion this high-impact team. You will evolve CAT, expanding its remit beyond traditional analytics & data science to create the data ecosystem for an AI age.

Your mission is twofold:

• Strategic Partner: Continue to lead the team as the indispensable source of truth for GDM’s leadership, using data to guide critical organisational decisions

• AI Data Architect: Lead the strategic evolution of the team's output, transitioning from traditional 'human-centric' analytics to a hybrid model that integrates “machine-centric” knowledge.

About Us

Artificial intelligence will be one humanity’s most transformative inventions. At Google DeepMind, we are a pioneering AI lab with world-class 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.

The Role

Key Responsibilities

Team Leadership & Strategic Steering

• Lead, mentor, and inspire a high-performing team of data scientists and analysts. Foster a culture of psychological safety, high agency, and continuous improvement

• Serve as a trusted advisor to GDM senior leadership. Proactively identify critical business questions and shape the team’s direction to meet those needs – acting as a first point of contact for the organisation’s most nebulous data challenges

• Manage performance and career growth, creating clear pathways for individuals to meet their personal and professional goals, while evolving & expanding skillsets to meet GDM’s organisational needs

Data Strategy

• Own and deliver an “organisational knowledge graph” charter – positioning it as an integrated data platform that acts as the central, trusted source of truth for agentic systems to access internal enterprise knowledge

• Define and execute a technical roadmap to balance the needs of human-led data science work, machine accessibility, and access for a wide user base across GDM. Architect the schemas and metadata layers that allow AI agents to correctly interpret business logic, disambiguate context, and retrieve accurate information (e.g., investing in NL2SQL readiness and RAG-optimised pipelines)

• Champion a "Data as a Product" mindset, where your team's data assets are managed with a product lifecycle, including versioning, SLOs, and clear documentation

• Invest in appropriate data governance and access management controls; ensure both assets and underlying data are well-governed, discoverable, and trustworthy (leveraging existing Google tools and knowledge where appropriate)

Technical Execution & Delivery

• Own the team’s overall portfolio of work – balancing opportunities for short-term impact and longer-term investment in new capabilities, investing in the right areas of GDM

• Partner with the wider Technical Operations & Analytics (TO&A) group leadership to integrate data across relevant product surfaces and deliver key cross-functional initiatives

• Maintain and deepen trust with existing stakeholders (e.g. Executives, StratOps partners, Compute managers, People & Culture, etc) to help them answer critical questions and increase efficiency and effectiveness of their groups with data

• Liaise with Google and Gemini teams to test the latest model and technical capabilities, forming partnerships where appropriate for joint success

Community Evangelism

• Lead and revitalise the GDM "Analytics Guild", fostering a wider community for data scientists and analysts across GDM and Google to share best practices, new tools, and critical learnings

• Act as the primary evangelist for the AI-first data mindset, helping to pull the entire data community forward

About You

In order to set you up for success as the Senior Manager, Business Data Strategy and Analytics at Google DeepMind, we look for the following skills and experience:

• Experience: Extensive technical background (e.g. Data Engineering, Analytics, or Data Science), including significant experience leading high-performing teams through technical transformations

• Strategic Acumen: Proven track record of using data to influence executive-level strategy.

• Technical Vision: You understand the modern data & AI stack. You have likely built or managed RAG pipelines, worked with Knowledge Graphs, or led transitions from BI to AI-ready data architectures – and have a strong vision to help the team deliver it

• The "Translator": You excel at bridging the gap, using your communication skills to align stakeholders from varied backgrounds around a common technical and product vision

• Governance & Empathy: Experience establishing governance in complex environments. You understand that "clean data" is a people problem as much as a technical one, and have demonstrated experience in orchestrating organisational efforts to maintain data quality and integrity

• AI Fluency: Ability and curiosity to use AI tools practically and effectively in your work, with a recognition and awareness of AI’s responsible use, risks, and limitations. Ability to leverage and promote AI for team and organisational productivity.

At Google DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact. We are committed to equal employment opportunity regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender

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