Senior Risk Analyst in London

Join our Economic Crime Modelling team and use advanced analytics to help protect our members and the Society from fraud, money laundering and other evolving financial crime threats. As a Senior Risk Analyst, you will lead the development, enhancement, monitoring, maintenance and governance of economic crime models across a range of domains in fraud and financial crime risk detection. The role combines traditional statistical modelling techniques with cutting-edge machine learning approaches to identify suspicious behaviours, emerging threats and hidden risk patterns.

You will lead engagement with fraud and financial crime analytics, technology and risk stakeholders to deliver innovative analytical solutions that strengthen the Society's financial crime detection capabilities and support a safe and secure banking environment. This is an exciting opportunity to apply advanced analytics and data science techniques to help protect customers and the Society from fraud and financial crime while shaping the future of economic crime risk management.

We are happy to consider flexible working approaches to help you perform at your best. At Nationwide we offer hybrid working wherever possible. More rewarding relationships are supported through our hybrid approach, bringing colleagues together across our UK wide estate, whilst also supporting generous access to home working. We value our time in the office to solve problems, to learn, and to feel connected. For this job you'll spend at least two days per week, or if part time you'll spend 40% of your working time, based at either our London, Swindon or Glasgow office.

If you’re based at our Glasgow office, this will apply from 1 April 2027 and ahead of that there will be a need to regularly connect with colleagues for collaboration events. If your application is successful, your hiring manager will provide further details on how this works. You can also find out more about our approach to hybrid working here.

Nationwide is committed to the redeployment of our employees impacted by change, as such applications for redeployment candidates will be prioritised in this recruitment process. If you’re a colleague on long‑term absence (for example, on parental leave) or a temporary worker, please use your personal email address to submit an application.

The extras you’ll get include:

• Private medical insurance
• A highly competitive pension to help you build a strong foundation for retirement
• Access to an annual performance-related bonus
• Training and development to help you progress your career
• A great selection of additional benefits through our salary sacrifice scheme
• Life assurance to provide peace of mind for you and your loved ones in the event of your death
• Wellhub – access to a range of free and paid options for health and wellness
• Up to 2 days of paid volunteering a year

As a Senior Risk Analyst, you will play a key role in developing and enhancing fraud and financial crime models across a range of economic crime risk areas. You will lead the analysis of large and complex datasets to identify suspicious behaviours and emerging threats, translating insights into practical improvements to financial crime detection. You will take ownership of complex modelling workstreams across the model lifecycle, including development, enhancement, implementation, monitoring and periodic review, applying appropriate statistical, machine learning and data science techniques and providing technical challenge to modelling assumptions.

Working closely with fraud and financial crime analytics, Risk, Technology, Operations and external vendors, you will investigate model performance and limitations, coordinate model changes and ensure robust testing and implementation readiness. You will produce high-quality analytical outputs, model documentation and monitoring reports, present findings and recommendations to governance forums, and respond to independent validation challenge. You will also ensure modelling activities comply with the Society’s Model Risk Management Framework and relevant regulatory expectations, including SS1/23, while proactively managing model risks, issues and remediation actions.

As a senior member of the team, you will provide technical guidance and mentoring to colleagues, lead peer reviews and help drive continuous improvement in modelling methods, standards and ways of working. We’re looking for an analytical and curious individual with experience of applying data, statistical or modelling techniques to practical business problems. You will be comfortable taking responsibility for defined analytical tasks, interpreting complex results and communicating your findings clearly.

The minimum requirements for this role are:

• Experience of developing or managing models for fraud detection, AML, transaction monitoring, customer risk assessment or network analytics
• Demonstrable experience of independently delivering complex analytical or modelling projects, translating business problems into effective solutions and actionable recommendations
• Strong programming and data manipulation skills using SAS, SQL, Python, R or comparable analytical tools, with experience of working with large, complex datasets
• Strong analytical judgement, including the ability to challenge assumptions, assess model limitations and recommend appropriate solutions
• Practical experience of developing, enhancing and monitoring statistical or machine-learning models, with a sound understanding of model performance assessment
• Communicate complex analytical findings clearly and confidently, influencing technical and non-technical stakeholders and presenting recommendations to decision‑making forums
• Take ownership of modelling workstreams, managing competing priorities, dependencies and risks while maintaining high standards of accuracy, documentation and delivery
• Provide technical guidance and mentoring to colleagues, contribute to peer reviews and promote knowledge sharing and continuous improvement
• Practical experience of model risk management, including producing model documentation, supporting independent validation and addressing governance findings
• Experience of applying regulatory expectations, including SS1/23, within model development, monitoring and lifecycle management

Our customer first behaviours put customers and members at the heart of how we work together. They are the set of behaviours that every colleague needs to display, in every role:

• Feel what customers feel
• Say it straight
• Push for better
• Get it done

You can strengthen your application by showing how our customer first behaviours resonate with you, and where you may have already demonstrated these.