Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Senior Liability Data Analyst - Scheme Transitions

Legal & General
Glasgow
1 week ago
Create job alert
Senior Liability Data Analyst - Scheme Transitions

Legal & General (L&G) is a leading UK financial services group and major global investor. We remain committed to safeguarding people’s financial futures while building a better society and creating value for shareholders. Our Institutional Retirement division protects the retirement benefits of over 700,000 customers through pension risk transfer solutions for UK and US defined‑benefit schemes.


Job Overview

We are seeking a Senior Liability Data Analyst to join the Scheme Transitions Team within our Award‑Winning Pension Risk Transfer business. In this role you will ensure the integrity and accuracy of pension scheme data, support the delivery of outstanding outcomes for our customers, and collaborate with stakeholders across the organization.


What You'll Be Doing

  • Managing operational data tasks including cleansing, validation, transformation, and integration
  • Consulting with internal stakeholders to understand data requirements and deliver tailored solutions
  • Collaborating with partners to improve data quality across systems
  • Testing and documenting processes to ensure consistency and reliability
  • Creating and maintaining audit trails for all data activities
  • Communicating key updates to internal teams and third parties
  • Supporting the development of junior team members through training and guidance
  • Contributing to the end‑to‑end delivery of Pension Risk Transfer transactions

Qualifications

  • Demonstrable experience working with Defined Benefit Pension schemes/scheme data
  • Strong technical aptitude and advanced Excel skills
  • Ability to effectively manage deadlines and prioritise work to meet timescales
  • Understanding of project management and testing frameworks
  • Knowledge of relevant legislation including GDPR and Treating Customers Fairly
  • A collaborative mindset and commitment to excellent customer outcomes
  • Ability to build strong relationships with both internal and external stakeholders

Benefits

  • Annual performance‑related bonus plan and share schemes
  • Generous pension contribution
  • Life assurance
  • Healthcare plan
  • At least 25 days holiday, plus public holidays and 26 days after 2 years’ service (holiday buying and selling options available)
  • Competitive family leave
  • Electric car scheme with tax‑efficient salary sacrifice option
  • Wide range of employee discounts on products and high‑street stores
  • Well‑designed office spaces that support collaboration and employee wellbeing

Additional Information

At L&G, we believe it is possible to generate positive returns today while building a better future for all. Joining us means becoming part of an inclusive culture that celebrates diverse backgrounds, views, and experiences. We offer flexible working options including part‑time, term‑time, and job shares, and we support development and career excellence through leadership and empowerment initiatives.


#J-18808-Ljbffr

Related Jobs

View all jobs

Senior Liability Data Analyst - Scheme Transitions

Senior Liability Data Analyst - Scheme Transitions

Senior Pension Data Analyst - Scheme Transitions

Senior Pension Data Analyst, Scheme Transitions (Hybrid)

Sr. Director of Master Data Management and Business Intelligence

Quantitative Analyst AVP

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.