Senior Data Strategy – Operations Lead

Role Overview

• Own and run the operational rhythm of the Data & Applied AI org: team syncs, roadmap reviews, OKR cycles, quarterly planning, and retrospectives.
• Lead the annual and quarterly planning processes for the team, linking data and AI initiatives to company-level goals and product strategy.
• Manage the VP's leadership calendar and key team meetings, including agenda setting, preparation of materials, coordination with presenters, and follow-ups for cross-functional reviews, executive updates, and offsites.
• Own the preparation cycle for leadership forums and company-wide reviews where the Data & Applied AI team presents: ensuring the right content, framing, and data are ready.
• Serve as the connective tissue between the Data & Applied AI team and Product, Engineering, Commercial, and other functions, ensuring priorities are aligned and dependencies are visible.
• Own stakeholder communication: regular updates, progress reports, and dashboards that give leadership and partner teams clarity on what the team is delivering and why.
• Represent the Data & Applied AI team in company-wide planning processes (e.g., product planning, OKR alignment, resource allocation).
• Track progress on key data and AI initiatives end-to-end, from scoping through delivery, identifying risks early and driving resolution.
• Support the VP in managing the team's portfolio of work: ensuring the right things are prioritised, resourced, and moving forward.
• Drive accountability across workstreams without being a bottleneck, using lightweight but effective tracking and reporting mechanisms.
• Continuously identify friction in how the team works, whether in processes, tooling, collaboration patterns, or information flow, and design practical improvements.
• Build and maintain scalable processes that help the team operate efficiently as it grows (e.g., intake workflows, documentation standards, knowledge sharing).
• Support headcount planning, resource allocation, and team capacity analysis with data-driven models.
• Lead or support high-impact strategic projects that span the Data & Applied AI org, such as evolving the team's operating model, defining AI adoption frameworks, or assessing build-vs-buy decisions for data infrastructure.
• Conduct analysis and research to inform key decisions: sizing opportunities, benchmarking approaches, or evaluating trade-offs.

Requirements

• 7+ years of experience in strategy, operations, or planning, ideally in a high-growth tech environment.
• Hands-on experience working closely with data, analytics, or AI/ML teams: you understand how these teams operate, what they deliver, and what slows them down.
• Technical familiarity: you can follow conversations about data pipelines, ML models, experimentation frameworks, and AI product features without needing everything translated.
• Proven track record running operating cadences (OKRs, roadmap reviews, business reviews) and driving cross-functional alignment in complex organisations.
• Strong program and project leadership: you take ambiguous, cross-functional problems from definition to delivery with minimal hand-holding.
• Excellent stakeholder management: you build trust with both technical and non-technical leaders, communicate with clarity, and know how to influence without authority, including executive leadership.
• Highly data-driven: comfortable building models, spreadsheets, and dashboards to inform decisions. SQL or BI tool experience (e.g., Looker, Tableau) is a plus.
• Exceptional bias to action: you keep momentum high, unblock work proactively, and know how to get things done in fast-moving environments.
• Strong written and verbal communication skills, with experience producing executive-level updates, presentations, and documentation.
• Proficient user of AI tools (e.g., ChatGPT, Claude, Copilot, Cursor): you actively use AI to accelerate your work, whether for drafting, analysis, research, or automation, and you stay current with how these tools are evolving.

Tech Stack

• SQL
• Tableau

Benefits

• Health insurance
• Flexible working hours
• Professional development opportunities