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Strategy & Operations Manager; Analytics

Job in Greater London, London, Greater London, W1B, England, UK
Listing for: Cleo AI
Full Time position
Listed on 2026-06-09
Job specializations:
  • IT/Tech
    Data Analyst, Business Systems/ Tech Analyst, Data Science Manager, Data Engineer
Salary/Wage Range or Industry Benchmark: 80000 - 100000 GBP Yearly GBP 80000.00 100000.00 YEAR
Job Description & How to Apply Below
Position: Strategy & Operations Manager (Central Analytics)
Location: Greater London

Requirements

  • 4+ years in a data-heavy strategy & ops, Biz Ops, product ops, analytics ops, data product, or similar role in a high-growth consumer tech environment
  • Fluent in SQL and comfortable working directly with data day-to-day (joins, aggregations, window functions, CTEs) - this is not a role for someone who is “data-driven” but relies on others to do the analysis
  • Demonstrated end-to-end ownership of cross-functional projects involving data and product (problem definition → design → implementation → rollout → iteration)
  • Comfortable operating at both the strategic/systems level (operating models, responsibilities, workflows) and deep in the detail (understanding a tracking issue, questioning a metric, reading a schema)
  • Experience managing projects/programmes with multiple stakeholders, technical & non-technical
  • Significant experience working closely with analytics / data teams: experimentation, product metrics, data quality, BI tools
  • Excellent communication and collaboration skills, with the ability to work effectively across all levels of seniority
  • Comfortable navigating change and ambiguity in a fast-moving environment
  • A team player with a proactive, problem solving mindset
  • (Desirable) Experience in a central analytics / data operations / analytics platform role
  • (Desirable) Experience with modern data stacks (e.g. dbt, Snowflake/Big Query, Looker/Mode, Amplitude/Mixpanel, experimentation platforms)
  • (Desirable) Experience building internal data/analytics products (self-serve tools, metrics layers, experimentation platforms, NLQ interfaces)
What the job involves
  • We’re creating a new Central Analytics function at Cleo; this role will be the founding hire
  • Central Analytics will be the backbone and amplifier of analytics at Cleo
  • It will own the shared systems and standards that embedded analysts rely on—things like event frameworks, experimentation tooling, shared metrics and taxonomies, self-serve capabilities — so product teams can move faster in shipping products that delight our users
  • Analytics is already one of the highest-impact teams at Cleo, shaping our biggest product decisions and delivering sharp, trusted insights across all areas of the company
  • Our mission is to take Analytics to the next level, building on our existing strength with exceptional systems, tooling and operational excellence
  • You’ll be taking on one of the highest-leverage building roles in Cleo’s data organisation
  • You’ll lead on the execution of this strategy; building the shared infrastructure and coordination layer that make Analytics and Cleo faster, more impactful, and more scalable
  • Reporting to the Director of Analytics, this role starts as a solo builder and is expected to grow into leading a small central team as we continue to scale. Your focus will be:
  • Building the Central Analytics function from scratch: defining what sits centrally; putting in place the standards and operating models that make the Analytics division stronger
  • Delivering high-leverage, cross-cutting initiatives end-to-end: leading data stack and infrastructure improvements that lift capabilities across the board
  • Getting hands-on with data and systems: using your technical fluency and SQL/python skills to validate decisions, shape tooling, and ensure the operational layer works
  • Lead end-to-end delivery of a small number of flagship, cross-cutting initiatives e.g LLM-driven natural language analytics system, event framework refactor, new experimentation tooling
  • Own shared analytics areas that do not sit cleanly with a single product team, such as central metrics, taxonomies, self-serve analytics workflows, and cross-team dashboards
  • Coordinate cross-pillar analytics work by surfacing overlaps, dependencies and gaps, and making sure shared problems have clear owners and momentum
  • Partner with Product, Engineering and Analytics Engineering to translate analytics needs into technical requirements and scalable solutions
  • Use SQL/Python to validate data, prototype metrics, test new tools, and improve data quality
  • Define and evolve the operating model for Central Analytics, with scope to hire and lead a small team over time
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