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We’re working with a large UK organisation operating in a high-volume, operationally complex environment that is continuing to strengthen how data is used to inform commercial and operational decisions. This role sits within an established Data & Analytics team and focuses on improving how performance data is interpreted and acted upon at senior levels. This position is designed for someone who enjoys working at the point where data meets decision-making. Rather than producing reports in isolation, you’ll be embedded in the business, helping leaders understand what’s driving performance and where attention should be focused.
Job Responsibility:
Analyse complex datasets to uncover trends, risks, and opportunities
Turn analysis into clear insight that supports commercial and operational decisions
Provide context around performance, productivity, margins, and forecasting
Work closely with senior leaders as a trusted analytical partner
Challenge assumptions and interpretations where data is being misunderstood
Help define what “good insight” looks like across the organisation
Enhance and evolve Power BI dashboards and analytical outputs
Ensure reporting is accurate, consistent, and aligned to finance standards
Support the move towards self-service analytics and reduced manual reporting
Partner with BI, data engineering, and governance teams
Contribute to trusted, standardised data models
Promote a single, reliable view of financial and performance data
Build and maintain models using SQL, Power BI, Databricks, and Excel
Apply strong understanding of P&L, margins, productivity, and forecasting
Requirements:
Strong background in data insight, analytics, or commercial/finance analysis
Hands-on experience with SQL and Power BI
Confidence working with financial and performance data
Experience in large or complex organisations with governed data environments
Proven ability to communicate insight to senior, non-technical stakeholders
Comfortable influencing decisions through insight rather than authority
Nice to have:
Experience within services, facilities management, retail, utilities, logistics, or similar operational sectors would be advantageous, but not essential