Pensions Data Analytics Graduate — Sep 2027 (London)

Lane Clark & Peacock LLP.

Greater London

Hybrid

GBP 28,000 - 38,000

Full time

9 days ago

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Benefits offered by this job

Study support
26 days leave + holidays
Private medical insurance
Wellbeing networks

Job summary

Lane Clark & Peacock LLP (LCP) is offering an Early Careers opportunity in London. You will join a team that blends analytical modelling with consulting support, handling data-driven pension scheme projects and client-facing deliverables.

The role focuses on developing technical skills through a structured graduate training programme, while collaborating with experienced professionals across project teams. A strong numeracy background and a 2:1 degree are desirable.

Qualifications

  • A Level Maths A Grade.
  • Degree 2:1 or currently studying for a degree in any subject.
  • Strong problem solving, numeracy and analytical skills.

Responsibilities

  • Data readiness assessment and data cleansing for pension schemes.
  • Build and run complex pensions models and rectify benefit calculations.
  • Draft client reports, advice and presentations with accurate figures.
  • Collaborate with project teams from analyst to partner level.
  • Support data readiness activities and ensure data aligns with client strategy.
  • Participate in internal and client meetings to drive project goals.
  • Contribute to data analysis and risk transfer considerations.
  • Assist with communications to clients and advisers on projects.

Skills

Analytical skills
Numeracy
Problem solving

Education

Degree 2:1 or studying for degree

Job description

Lane Clark & Peacock LLP (LCP) is offering an Early Careers opportunity in London. You will join a team that blends analytical modelling with consulting support, handling data-driven pension scheme projects and client-facing deliverables.

The role focuses on developing technical skills through a structured graduate training programme, while collaborating with experienced professionals across project teams. A strong numeracy background and a 2:1 degree are desirable.

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