Senior Quantitative Analyst

mgpru; Greater London; Hybrid; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Pension scheme

Share Save plan

38 days annual leave

Job summary

M&G is seeking a Senior Quantitative Analyst in London to drive quantitative analysis for the Life Investment Office. You will design models, assess portfolio risk and guide asset allocation for multi-asset portfolios.

You will collaborate with the Quantitative Portfolio Design team and other investment colleagues to translate complex analytics into actionable insights and robust investment tools.

Qualifications

• Strong quantitative background in mathematics, statistics, physics, CS, financial engineering or economics.
• Significant experience in quantitative investment, portfolio construction or risk modelling.
• Advanced Python skills and developing reliable analytical tools.

Responsibilities

• Develop and maintain quantitative models and analytics for Strategic Asset Allocation and Reference Portfolios.
• Perform portfolio analysis to assess risk, return and trade-offs across multi-asset portfolios.
• Build diagnostics and insights to support senior investment decisions, with robust testing and governance.

Skills

Quantitative analysis

Python

Portfolio risk

Communication

Analytical thinking

Education

Degree in related field

Tools

Python

Job description

At M&G, our purpose is to give everyone real confidence to put their money to work. With a heritage dating back more than 175 years, we have a long history of innovation in savings and investments, combining asset management and insurance expertise to offer a wide range of solutions.

Our two distinct operating segments, Asset Management and Life, work together to provide access to balanced, long-term investment and savings solutions.

Through telling it like it is, owning it now and moving it forward together with care and integrity; we are creating an exceptional place to work for exceptional talent.

We will consider flexible working arrangements for any of our roles and offer workplace adjustments to ensure you have the support you need to succeed in your role.

Senior Quantitative Analyst

The Life Investment Office (LIO) is responsible for approximately £159bn of assets, including the UK's largest £134bn With Profits Fund, delivering multi-asset and annuity solutions on behalf of the Prudential Assurance Company (PAC). The LIO has deep expertise across asset allocation, manager selection and oversight, strategy design, derivatives and portfolio management. By combining scale, experience and global partnerships, LIO focuses on building resilient, diversified portfolios designed to deliver long-term value for clients.

The Senior Quantitative Analyst will play an important role in developing the models, analytical tools, and quantitative frameworks used to support portfolio design and investment decisions of the Life Investment Office. The role will support Strategic Asset Allocation, Reference Portfolio design and broader portfolio construction and risk analysis across LIO's multi-asset portfolios.

The successful candidate will combine strong quantitative and technical skills with practical investment judgement. They will develop robust analytical frameworks and tools, assess portfolio risks, trade-offs and sensitivities, and translate quantitative analysis into clear insights for investment decision-making.

The role will involve independently delivering complex quantitative analysis and modelling within agreed investment priorities, working closely with members of the Quantitative Portfolio Design team and colleagues across Investment Office. They will also contribute to the continued development of the team's analytical capabilities.

Key Responsibilities

• Support the development of Strategic Asset Allocation and Reference Portfolios across LIO's multi-asset portfolios
• Undertake quantitative portfolio analysis to assess risk and return characteristics and portfolio trade-offs
• Develop portfolio optimisation, scenario analysis and robustness-testing capabilities to support portfolio construction and investment decisions
• Evaluate the impact of investment assumptions, portfolio constraints and implementation considerations on portfolio outcomes
• Develop clear portfolio diagnostics and analytical outputs, translating complex quantitative analysis into insights for senior investment decision-making
• Develop and maintain quantitative models and analytical tools, primarily using Python, with appropriate testing, documentation and version control
• Critically evaluate quantitative models and methodologies, understanding their limitations and applying practical investment judgement when interpreting results

Requirements & Experience

• A strong quantitative academic background in mathematics, statistics, physics, computer science, financial engineering, economics or a related field
• Significant experience in quantitative investment, portfolio construction, risk modelling or a closely related area
• A strong understanding of multi-asset portfolio analysis, investment risk and portfolio-construction techniques
• Advanced Python skills and experience developing reliable analytical tools and processes
• The ability to apply and critically evaluate quantitative models, understand their limitations and exercise appropriate investment judgement
• Strong analytical and problem-solving skills, with the ability to structure and address complex or ambiguous investment questions
• The ability to communicate technical concepts clearly and work effectively with both technical and non-technical colleagues and stakeholders
• High standards of accuracy, transparency, documentation and governance

Location: London

Work Level: Manager / Expert

What we offer:

• A valuable pension scheme of up to 18% (13% made up of employer contributions and 5% employee contributions).
• Access to our Share Save and Share Incentive Plan, alongside financial wellbeing and support services to help give you real confidence to put your money to work.
• Enjoy 38 days annual leave (including bank holidays), with t