Senior Data Analyst

We're hiring a Senior Data Analyst.

This is not a reporting-only role. Embedded day to day within our commercial team, you'll be responsible for the core metrics that matter to the business - conversion rate, contracted volume, total sales, and margins - building on the pipeline tracking, forecasting and partner reporting that already exists. Priorities are set jointly with commercial; performance and development sit with the Analytics Manager, who you'll report into.

As a senior analyst, you'll take ambiguous commercial questions, decide the right approach, and turn analysis into clear recommendations rather than just presenting numbers. Success isn't measured by dashboards shipped - it's measured by whether stakeholders have metrics they understand and trust, analysis that changes what people do, and a team that can increasingly self-serve the answers it needs.

Responsibilities

Pipeline & Revenue Forecasting Accuracy

• Monitor the sales pipeline, catching and resolving cases where in-progress and confirmed revenue overlap or deals get double-counted.
• Define and report on forecast accuracy against annual targets, setting the standard for how commercial metrics are tracked across the team.
• Diagnose CRM data quality issues, such as parent-child asset relationships, that put pipeline and forecast reliability at risk.

Commercial Analysis & Insight

• Carry out commercial opportunity sizing and partner performance analysis to support sales and leadership decisions.
• Identify underperformance, emerging trends and risks in the pipeline before they surface in headline forecast numbers.
• Serve as the voice of data for the commercial team, translating complex analysis, including retention and renewal trends, into clear recommendations for senior stakeholders.

Partnership & Storytelling

• Work directly with commercial and sales stakeholders to understand what "good" looks like for their metrics, and translate that into clear, agreed definitions.
• Translate complex data into clear, compelling stories that inspire action among non-technical stakeholders.
• Increase data adoption across the commercial team so non-technical colleagues can self-serve for routine needs.

Requirements

Must haves

• Solid SQL skills, used to investigate complex datasets across modern analytics stacks (e.g. dbt, Omni or similar BI tools).
• Good commercial understanding, with an ability to connect analytical findings to revenue and margin outcomes.
• Experience developing forecasts or scenario models, and explaining the drivers behind variance from actuals.
• Ability to turn ambiguous stakeholder questions into well-defined analytical problems, and to present recommendations clearly to senior stakeholders.
• Proven experience building trusted metrics or reporting from messy or inconsistent source data (e.g. CRM, transactional systems).

Bonus points

• Experience in energy, fintech, or another commercially complex, data-heavy sector.
• Python for deeper statistical or data-quality work.
• Experience building metric frameworks that connect operational activity to commercial outcomes.
• Familiarity with CRM systems and parent-child/account hierarchy data structures.