Senior Data Analyst

Job Title

Senior Data Analyst (Service Delivery & AI Analytics)

Department

Service Delivery

Location

Remote or Hybrid (split between site-based and home-working)

Country

Flexible (UK/EU/US/Hong Kong)

Level

Individual Contributor

Reports to

Global Head of Service Delivery, IT & Repairs

Contract Type

Permanent / Full-time

Contracted Hours/Days

37.5 hours / 5 days per week

Date:

29/01/26

About Us

At Reveal, passion meets purpose. Our body-worn video solutions are more than just technology; they're a testament to our commitment to safety, innovation and change. Rooted in the UK, we've become a trusted ally for many police forces, local authorities, retailers and private organisations; helping to pioneer and drive the application of body-worn video in settings and geographies where we can see exciting potential.

With an influence now spanning over 40 countries, our mission to make a positive impact continues to gain momentum.

Purpose of the Role The Senior Data Analyst will play a critical role in enabling data-driven decision-making across Reveal’s global service organisation. This role is responsible for extracting, transforming, analysing, and visualising data from multiple enterprise systems—including Azure, Salesforce, Halo ITSM, and repair/logistics platforms—to deliver high-quality insights for senior executives, sales teams, service delivery, engineering, product teams, and customers.

The role will design and maintain advanced Power BI dashboards, build robust data models, perform historical trend analysis, and develop forecasting and pattern-detection models to support operational planning and continuous improvement.

In addition, this role will contribute to the evolution of AI-enabled analytics, using Python and modern AI tools (e.g. Copilot and ChatGPT-style agents) to enhance insight generation, automate analysis, and enable self-service reporting capabilities across the business.

This role is critical to Reveal’s ability to scale service operations globally while maintaining service excellence, customer trust, and commercial performance. By combining advanced analytics, automation, and emerging AI capabilities, the Senior Data Analyst will help transform data into a strategic asset across the organisation.

Key Responsibilities The following outlines the principal responsibilities of the role. This list is not exhaustive and may be updated to reflect business needs, provided it remains aligned with the overall purpose of the position.

Data Extraction & Integration

• Design, build, and maintain reliable data pipelines to extract data from Azure, Salesforce, Halo ITSM, and other internal or third-party systems.

• Develop automated ETL processes to ensure timely, accurate, and scalable data refresh cycles.

• Work with development teams and system owners to integrate data via APIs and improve data availability.

Data Modelling & Analytics

• Build and maintain robust data models to support operational, commercial, and executive reporting.

• Analyse service delivery performance including SLAs, KPIs, MTTR, incident volumes, backlog trends, repair cycle times, and device failure patterns.

• Perform historical trend analysis and develop forecasting models to support capacity planning, staffing decisions, and risk identification.

• Identify patterns, anomalies, and systemic issues that impact service quality or cost-to-serve.

Dashboarding & Reporting

• Design and deliver high-quality Power BI dashboards tailored to different audiences, including senior executives, sales teams, service operations, and customers.

• Standardise KPI definitions and reporting structures across regions (UK, Germany, US, Hong Kong).

• Automate recurring reports and reduce reliance on manual, spreadsheet-based reporting.

• Ensure dashboards tell a clear, actionable story rather than simply presenting data.

AI-Enabled Analytics & Automation

• Use Python to automate data processing, analysis, and reporting workflows.

• Contribute to the design and development of AI-assisted analytics solutions, including:

• Copilot-style or ChatGPT-based agents to support insight generation, reporting, or operational queries

• Natural-language interfaces for exploring service data

• Partner with stakeholders to identify high-value use cases where AI can enhance decision-making or operational efficiency.

Continuous Improvement & Decision Support

• Provide analytical