Quantitative Analyst

Company Description

Legal & General (L&G) is a leading UK financial services group and major global investor.

We’ve been safeguarding people’s financial futures since 1836, and strive to build a better society, while improving the lives of our customers and creating value for shareholders.

We are one of the world’s largest asset managers and provide powerful asset origination capabilities. Together, these underpin our retirement and protection solutions: we are an international player in pension risk transfer, in UK and US life insurance, and in UK workplace pensions and retirement income.

L&G Institutional Retirement looks after around 700,000 institutional customers who have their retirement benefits secured with us. Operating continuously in the UK market from our entrance in 1987, we are the UK’s longest-running insurer.

Our Institutional Retirement business is the UK’s longest-serving active bulk annuity provider.

Who we are

Institutional Retirement is the only insurer to have been operating continuously in the UK market from our entrance in 1987 to the present day. Our UK retirement annuity book stands at an estimated £86.1 billion at 31 December 2023.

Across our retail and institutional retirement businesses, we look after more than 1 million customers, around c.700 000 of whom are institutional customers who have had their retirement benefits secured with us.

We’re looking for a Quantitative Analyst to join our Investments Quantitative team at L&G Institutional Retirement.

The Investments Quantitative team support the different areas of the wider Investments and Institutional Retirement teams (e.g. New Business, Asset Liabilities Management, Portfolio Management, Structuring, Finance, Risk) with both long‑term strategic technology projects and tactical solutions, through quantitative model/tool development and analyses, primarily using Python. These models are used for fixed‑income asset and pension liabilities modelling, optimising portfolio to maximise return/reduce risk, portfolio management and risk analytics, and capital/SCR modelling.

You’ll work with other members of the team in developing solutions to highly technical problems. They will be key in ensuring that solutions are accurate and well‑tested, and will work closely with the business to both support and improve tools.

• Developing and enhancing a range of financial models using Python, supporting fixed‑income asset and pension liabilities modelling, portfolio optimisation, portfolio management, risk analytics and capital/SCR modelling.
• Proactively improving existing tools and processes, including calculation efficiency, use of new libraries or techniques, code quality and testing.
• Supporting processes and tools with the aim of removing manual handovers and reducing duplication.
• Supporting relevant Investments teams in their day‑to‑day use of tools, troubleshooting issues, advising on methodology and implementing suggested improvements or enhancements.
• Taking ownership of platform issues that affect the use of tools and escalating with relevant in‑house and vendor teams to achieve resolution.
• Ensuring business and system changes follow best business practices and comply with the IT Change Management Standard.
• Working with team members to develop solutions to highly technical problems and ensuring these solutions are accurate and well‑tested.
• Working closely with the business to support and improve tools used across the wider Investments function.

• Python development experience, including use of Num Py, Sci Py, Pandas or Polars.
• Strong programming skills and understanding of computer science fundamentals such as algorithms, data structures and complexity.
• Understanding of key financial engineering concepts such as no‑arbitrage principles, risk‑neutral methods, vanilla derivative pricing and VaR.
• Familiarity with portfolio analytics, portfolio management and relative value assessment.
• Experience developing applications or large Python libraries and interfacing Excel with Python (COM or xlwings).
• Experience with SQL, Snowflake or similar platforms, with cloud‑based development or VBA…