Reward Analytics Data Analyst (Hybrid)

Medical Protection Society; Leeds; Hybrid; GBP 38,000 - 64,000; Full time

Benefits offered by this job

Pension 11%

25 days annual leave

Private medical cover

Death in service 6x salary

Wellbeing support

Hybrid working

Inclusive culture

Job summary

Medical Protection Society (MPS) is seeking a highly analytical Data Analyst to transform pay and payroll data into actionable insight, supporting reward decisions and workforce planning. You’ll turn complex data into clear narratives that influence pay reviews and workforce planning.

Collaborating across HR and Finance, you’ll shape pay strategies, develop dashboards and reports for the Reward team, explain data meaning, and present recommendations to drive action within a flexible

Qualifications

• Advanced Microsoft Excel skills, including complex formulas, lookups, PivotTables, data reconciliation and analytical reporting.
• Ability to explain what the data means and build a compelling narrative from data.
• Experience in trend analysis and scenario modelling for pay/reward contexts.

Responsibilities

• Producing insightful analysis and reporting on pay, payroll and colleague data
• Building models to support pay reviews and reward related projects
• Conducting trend analysis, scenario modelling and financial impact assessments
• Turning complex data into clear recommendations and business insights
• Creating engaging reports that help stakeholders understand the story behind the data

Skills

Advanced Excel

Analytical thinking

Storytelling with data

Communication

Tools

PivotTables

VLOOKUPs

Data reconciliation

Job description

Medical Protection Society (MPS) is seeking a highly analytical Data Analyst to transform pay and payroll data into actionable insight, supporting reward decisions and workforce planning. You’ll turn complex data into clear narratives that influence pay reviews and workforce planning.

Collaborating across HR and Finance, you’ll shape pay strategies, develop dashboards and reports for the Reward team, explain data meaning, and present recommendations to drive action within a flexible