Quantitative Analyst

Job Description

We have an exciting and unique opportunity for a Fixed Income Quantitative Analyst to join a successful, highly-regarded team within LGIM. This role will contribute to the development of both systems infrastructure and quantitative fixed income models to support the investment, risk and attribution capabilities of the teamWhat you'll be doingDeveloping and continually enhancing the data and model platform and associated analytics used to support investment, risk, attribution, new business development and new asset classes Contributing to the development of quantitative fixed income models and associated governance framework to support investment, risk, attribution and pricing portfolio construction Working with the portfolio management to deliver robust, relevant and scalable analytical solutions Building intellectual capital by performing strategic research and analysis that applies the latest financial knowledge to topical issues in the industry while working with other team members Taking part in IT systems projects and business process projects that affect the team and related business areas Ensuring effective utilisation of enhanced data, analytical, risk engine and portfolio management capabilities Collaborating with associated teams (e.g. collateral management/margining; derivative pricing) to ensure new operational/business processes are implemented in the most effective way Supporting investment analysis relevant to the client balance sheet and the Investment Management Agreement Ensuring relevant instruments are priced and analysed in line with market conventions and methods and can be reported on appropriately To include evaluating actual and potential collateral use where products are collateralised or margined Ensuring that any actions taken with respect to managing client portfolios are in accordance with LGIM’s Treating Customers Fairly policy Qualifications Strong fixed income modelling knowledge including derivatives across credit, rates and inflation .NET, Python, Matlab or C# programming experience  Good knowledge of risk management practices and practical constraints in implementation Understanding of a broad range of investment management concepts such as efficient frontiers, capital asset pricing model, active vs. index, etc. High degree of proficiency with IT including strong programming skills in at least one language Knowledge of the regulatory and legislative landscape as it relates to pension schemes and to de-risking Prior exposure to work involving pension schemes and/or insurance clients Ability to execute quickly on client projects including data gathering and validation Building and maintaining models for pricing, portfolio construction and portfolio management of derivative strategies designed to hedge risks and enhance returns Additional InformationLegal & General is a leading financial services organisation, named in 2023, for the second year running. Rated top in our sector and top for inspirational leadership, we have a strong heritage and an exciting future. We’re one of the world's largest asset managers, homebuilders, pension providers and insurers. Connecting to form a unique business model which drives value for our customers and society. And enabling our people to create impact through work that is meaningful and valued. If you join us, you’ll be part of a welcoming, inclusive culture, with opportunities to collaborate with people of diverse backgrounds, views, and experiences. Guided by leaders with integrity who care about your future and wellbeing. Empowered through initiatives which support people to develop their careers and excel. We strive to be open, mindful, and inclusive, so are always willing to discussing flexible working arrangements and reasonable accommodations for candidates with specific needs. It doesn’t matter if you don’t meet every single criterion in this advert. Instead, think about what you excel at and what else you can bring in terms of strengths, potential and connection to our purpose. If you’re open to find out more, we'd love to hear from you. Share this article