Pensions De-Risking Analyst: Data, Risk & Delivery

Aptia Group; Manchester; On-site; GBP 35,000 - 52,000; Full time

Job summary

Aptia Group in the UK is seeking a De-Risking Analyst to support pension de-risking projects for major schemes. You will assist with data analysis, DB pension calculations, and stakeholder engagement to ensure accurate, efficient delivery within budgets and timelines.

The role emphasizes close collaboration with project teams, clients, and offshore colleagues, with a focus on data quality and process rigor.

Qualifications

• At least 1–3 years’ experience in UK Pension Administration.
• Experience with DB pension calculations and member data.
• Pensions project experience is a plus.
• Strong analytical, numerical, and problem-solving skills.
• Excellent attention to detail and communication.

Responsibilities

• Support the delivery of pension de-risking projects on time, within budget and to a high standard.
• Perform and review DB pension calculations and member data analyses.
• Execute and peer review project work, identifying risks and maintaining data quality.
• Help prepare project documentation, including engagement and non-reliance letters.
• Monitor project progress and escalate delivery or budget risks as needed.
• Support project billing and budget tracking activities.
• Build strong relationships with clients and stakeholders and provide updates.
• Collaborate with offshore teams to coordinate project activity.
• Assist in resolving data issues, errors, omissions and client complaints.

Skills

Pension Administration

Data analysis

Stakeholder management

Attention to detail

Analytical thinking

Job description

Aptia Group in the UK is seeking a De-Risking Analyst to support pension de-risking projects for major schemes. You will assist with data analysis, DB pension calculations, and stakeholder engagement to ensure accurate, efficient delivery within budgets and timelines.

The role emphasizes close collaboration with project teams, clients, and offshore colleagues, with a focus on data quality and process rigor.