Quantitative Risk Strategist

Rothesay is the UK’s largest pensions insurance specialist, purpose-built to protect pension schemes and their members’ pensions. With over £69 billion of assets under management, we secure the pensions of nearly one million people and pay out, on average, approximately £350 million in pension payments each month.

Rothesay is dedicated to providing excellence in customer service alongside prudent underwriting, a conservative investment strategy and the careful management of risk. We are trusted by the pension schemes of some of the UK’s best known companies to provide pension solutions, including British Airways, Cadbury’s, the Civil Aviation Authority, the Co‑Operative Group, National Grid, Nat West, Morrisons and Telent.

At Rothesay, we are striving to transform our industry. We believe deeply in creating real security for the future and our leadership in finding new and better ways to do that is the key to our success. To do that, we need the very brightest original thinkers to bring creativity as well as rigour. Rothesay is a rewarding place to work, where quality people can thrive and prosper.

We pride ourselves on the connections our people build, many of whom have been with us for over ten years.

Head of Risk Strategists

Permanent

Conduct

The Model Risk Management (MRM) team is a critical function within the Chief Risk Officer (CRO) organisation. The team is responsible for identifying, assessing, and mitigating risks associated with the use of models across the firm. This includes conducting independent model reviews, validating methodologies, and ensuring compliance with regulatory standards. MRM plays a key role in maintaining the integrity of the firm's modelling framework, providing transparency to stakeholders, and supporting informed decision‑making by ensuring models are robust, reliable, and aligned with business objectives.

• Assess and analyse conceptual soundness of current models, including capital and pricing calculators as well as calibration methodologies, by performing independent reviews to validate and verify their intended use.
• Understand model purpose, the underlying mathematical model assumptions, its implementation and its limitations. Understand the model behaviour under stress such as applied in capital calculations. Analyse the implementation of models in Python and Rust, identifying potential inefficiencies or inaccuracies
• Develop and implement alternative model benchmarks and compare the outcome of various models. Based on the validation methodology, recommend ways to improve the implementation. Leverage Python and Rust to create robust benchmarking tools and frameworks for model comparison.
• Conduct independent quantitative and qualitative research, extracting and processing data to evaluate model effectiveness; this can include the designing of new model performance metrics and assurance tests. Utilise libraries such as Num Py, Pandas, and Sci Py for data processing and performance metric design.
• Written and verbal communication of validation work.
• Capture existing and on‑going model validation work. Ensure validation work is captured in a structured and version‑controlled manner, using tools like Git.
• Report on the current state of validation and assurance of models.
• Structure model documentation, extending documentation where necessary, with the strat team to meet basic model documentation standards. Ensure documentation includes technical details of model’s implementations, with clear explanations of algorithms and code structure.
• Aid new modelling by providing coding reviews and proposing model improvements.
• Carry out model risk management tasks with a view to the auditability of model assurance as well as perform any task associated with model risk management as required.

What is essential and what is nice to have?

• PhD degree in quantitative sciences, with a focus on applied mathematics, statistics, or computational methods.
• Good grounding in basic mathematics and statistics, and numerical methods.
• Proficiency in Python programming, including experience with…