Role overview
The Senior Performance Analyst will lead the day-to-day performance analysis for projects and services, helping teams understand what is working, what needs to improve and how success should be measured. The role requires strong analytical judgement, clear communication and the ability to guide others.
You will work with multidisciplinary teams across data, AI, software engineering, product, QA and delivery to create practical outcomes for clients and end users.
Key responsibilities
- Design and maintain performance measurement frameworks, including KPIs, goals, user needs and benefits measures.
- Carry out complex analysis using multiple data sources and translate findings into clear recommendations.
- Develop dashboards, reports and visual stories that communicate service performance to different audiences.
- Lead quality assurance of performance data, including cleansing, validation and explanation of limitations.
- Work closely with product, delivery, user research, data and client teams throughout the product life cycle.
- Support, delegate to and upskill other analysts where appropriate.
Essential skills and experience
- Strong experience in digital or service performance analysis, including KPI design and reporting.
- Proficiency in analytical tools and the ability to apply a range of techniques to service data.
- Ability to communicate complex data as compelling, accessible and actionable insight.
- Understanding of product or service life cycles and how measures change across discovery, delivery and live service.
- Experience integrating quantitative data with user research, surveys or other qualitative evidence.
- Good knowledge of data privacy, security and analytical quality assurance.
Desirable skills and experience
- Experience with Power BI, GA4, SQL, Python, R or similar analytics tools.
- Experience mentoring junior analysts or improving analytical processes.
- Experience in Agile, public-sector or user-centred digital delivery.
What success looks like
- Complex analysis is converted into practical recommendations.
- Teams have reliable measures for progress, value and user outcomes.
- Analytical processes are repeatable, assured and continuously improved.