Homes England | National Housing Bank
£59,631 - £69,548 | Location: Hybrid 50/50 Our new Headquarters are in Leeds but colleagues can be based in any of our offices (Leeds, Newcastle, Manchester, Liverpool, Birmingham, Bristol, Northstowe)
Homes England is launching the National Housing Bank, a new government-backed investment platform to accelerate housing delivery across England.
With £16bn in capital, it will unlock private investment, support regeneration and accelerate housing delivery across the UK. Joining now offers a rare opportunity to shape a major new national investment platform from the ground up.
Homes England is the government’s housing and regeneration agency. It uses grant, land, lending, equity investment and guarantees to increase housing supply and support regeneration across England. Homes England also manages the existing Help to Buy equity loan portfolio. Its subsidiary, the National Housing Bank (NHB), provides lending, equity investment and guarantees to support housing delivery. Together, Homes England and the NHB require robust quantitative analysis to understand and manage financial risk across a large and diverse portfolio.
The Quantitative Risk and Stress Testing team is looking for an experienced quantitative professional to develop, maintain and operate analytical tools and financial risk models that help the business quantify, understand and manage financial risk.
The postholder will independently deliver defined modelling and analysis, using established methodologies and exercising sound judgement. This includes portfolio analysis, model development and operation, stress testing, scenario analysis and reporting using economic forecasts, market data and portfolio performance data.
Working under the technical direction of the Quantitative Analyst, the postholder will contribute to the development, validation and implementation of a range of financial risk forecasting models used for economic capital, credit risk, stress testing and portfolio risk assessment.
The opportunity
Responsibilities include:
- Support the development, maintenance, and operation of quantitative financial risk models, primarily using Python and SQL, including models relating to Value at Risk (VaR), cashflow forecasting, credit risk parameters (PD, EAD, LGD), Expected Credit Loss (ECL), Economic Capital, and Monte Carlo simulation.
- Independently undertake quantitative analysis of the organisation’s financial portfolio, importing data, running models, assessing risk exposures, performance analysis, and identification of emerging risks or vulnerabilities.
- Lead the execution of financial risk modelling, running models under a range of economic and financial assumptions and producing robust analysis to assess financial resilience.
- Own and manage datasets used in quantitative modelling, ensuring that data is appropriately structured, validated, and maintained to support reliable analytical outputs.
- Work with finance, investment teams, and digital to source and integrate data required for modelling, including economic forecasts, market data, portfolio performance data, and external benchmarks.
- Apply appropriate statistical and analytical techniques to large datasets, exercising judgement in the selection of methodologies and interpretation of results.
- Maintain clear documentation of data sources, model inputs, assumptions, and analytical processes, supporting transparency and good model governance.
- Prepare clear and accessible analysis and reporting. Develop and maintain automated reporting solutions and dashboards (e.g. Power BI) to communicate model outputs across the organisation.
- Support compliance with relevant regulatory and accounting requirements, including analytical processes supporting IFRS9 reporting and portfolio risk monitoring.
- Contribute to the ongoing improvement of quantitative models, analytical tools, and data processes, working with the senior Quantitative Analysts to enhance modelling capability.
- Support wider financial and analytical modelling across the organisation, reviewing and contributing to analytical work where appropriate.
- Remain informed of developments in quantitative finance, data science, and financial risk analysis, applying relevant techniques where appropriate.
- Flexible, agile and able to effectively pivot activity as operational requirements develop and effectively manage competing business needs.
Candidate profile
- Outstanding numerical and analytical ability, supported by a masters degree in a highly quantitative field such as Mathematics, Statistics, or Physics, or equivalent significant professional experience.
- Proven track record in a similar quantitative analytical role, with significant exposure to financial risk modelling, portfolio analysis, and related quantitative analysis.
- Strong programming skills in Python and SQL, with experience developing and maintaining analytical tools and quantitative models.
- Advanced Microsoft Excel capability, including use of complex functions for data manipulation, analysis, and modelling, data sources, and VBA.
- Experience working with modern analytical development environments, such as VS Code, Databricks, SQL-based platforms, Azure DevOps (ADO), and Git, or similar tools used in collaborative model development.
- Good understanding of the quantitative modelling lifecycle, including model development, testing, documentation, and maintenance within an appropriate governance framework.
- Strong organisational skills and attention to detail, with the ability to manage multiple analytical tasks and deliver high-quality outputs to agreed timelines.
- Extensive experience of delivering regular portfolio analysis and creating and managing automated reporting (e.g. using Power BI).
- Collaborative working style, with the ability to work effectively with colleagues across risk, finance, digital, and analytical teams.
- Strong communication skills, including the ability to explain analytical findings clearly to non-technical stakeholders through written reports, presentations, and visualisations.
- Commitment to continuous improvement, including identifying opportunities to enhance analytical approaches, models, and data processes.
- Ability to work independently while collaborating closely with senior analysts and subject matter experts, demonstrating sound judgement in analytical work.
- Desirable: Familiarity with financial risk modelling frameworks and regulatory standards (e.g., IFRS 9, Basel frameworks, or similar).
- Desirable: Knowledge of the real estate sector, particularly the housing market in England.
- Desirable: Experience working within or alongside government or public sector organisations.
Why join?
- Help build a new national investment institution
- Work on complex housing and regeneration transactions
- Deploy £16bn of government-backed capital
- Hybrid 50/50 working across multiple national locations
- Defined benefit pension and strong public-sector benefits
Contact point for applicants
Name : Rebecca Nolan
Email : [1]
[email protected]
Recruitment team
Email : [2]
[email protected]
Closing date: 13th July 2026
Right to Work in the UK is required.
References
Visible links
1. mailto: [email protected]
2. mailto: [email protected]