Compensation Specialist
Location: London (4-5 days per week on-site)
Salary: Competitive
About the Opportunity
Our client is a high-performing international organisation operating within a fast-paced, data-led environment. As the business continues to expand across multiple markets, they are investing in the evolution of their Reward function and are seeking a Compensation Specialist to support and enhance key compensation programmes across the organisation.
This is a broad and commercially focused role that combines day-to-day compensation activity with analytics, benchmarking, process improvement and strategic reward projects. The successful candidate will play an important role in helping the business make informed compensation decisions, improving data quality and reporting capabilities, and supporting the development of a modern, technology-enabled Reward function.
Unlike traditional compensation roles that focus heavily on administration, this opportunity offers direct exposure to senior stakeholders, involvement in business-critical projects, and the chance to influence how compensation practices evolve within a growing international organisation.
Key Responsibilities
- Support compensation activities across the employee lifecycle, including hiring, internal mobility, reward reviews and employee exits.
- Assist with the planning, delivery and governance of annual and off-cycle compensation review processes.
- Analyse compensation and workforce data to identify trends, risks, insights and areas for improvement.
- Validate compensation proposals and maintain high standards of data accuracy, governance and confidentiality.
- Lead or contribute to reward-related projects, including benchmarking, job architecture development and pay transparency initiatives.
- Design and enhance reward reporting, dashboards and analytics capabilities to support business decision-making.
- Collaborate with HR, Finance and business stakeholders to provide compensation insights and recommendations.
- Support the adoption of new technologies and AI-enabled solutions to improve reward processes, analysis and reporting.
Candidate Profile
The ideal candidate will bring hands-on compensation experience gained within a fast-moving and commercially focused organisation. They will be naturally analytical, comfortable working with large datasets, and motivated by the opportunity to influence compensation strategy and decision-making.
You must have:
- Have a background working within buy-side Financial Services (Hedge fund or Asset Management ideally) or Tech.
- Experience supporting compensation programmes across multiple employee lifecycle events.
- Strong understanding of compensation review cycles, reward recommendations and governance processes.
- Experience using compensation benchmarking data and market intelligence to inform reward decisions.
- Demonstrable ability to analyse large volumes of data and translate findings into meaningful insights.
- Excellent attention to detail, particularly when handling sensitive and confidential information.
- Strong stakeholder management and communication skills, with the ability to present data and recommendations clearly.
- Experience contributing to pay transparency, reward transformation or job architecture initiatives.
- The ability to thrive in a dynamic, evolving environment where priorities can change quickly.
The following would be advantageous:
- Exposure to Workday Advanced Compensation or similar reward systems.
- Experience creating dashboards and data visualisations using Power BI, Tableau or comparable tools.
- Working knowledge of SQL, Python or other analytical technologies.
- Experience leveraging AI-enabled tools to improve reporting, analysis or process automation.
This position offers an exceptional opportunity to join an ambitious organisation where reward is viewed as a strategic business lever. The successful candidate will gain exposure to complex compensation challenges, work closely with senior stakeholders, and contribute to the ongoing development of a forward-thinking Reward function.