Credit Risk Analyst

Are you a numerically minded graduate or early-career analyst who enjoys solving problems, investigating patterns and understanding the story behind the data?

At Castle Trust Bank, we pride ourselves in being a fintech challenger bank, providing specialist property mortgages, retail finance lending and savings accounts to a variety of customers. 

We’re looking for a Credit Risk Analyst to join our Risk function at Castle Trust Bank. This is an excellent opportunity to develop hands-on experience across credit risk analytics, IFRS 9 model monitoring and model development within a growing specialist bank.

You’ll work with data held in our Databricks environment, helping the team understand changes in portfolio and model performance. From investigating behavioural shifts and testing model enhancements to producing analysis for senior stakeholders, you’ll gain exposure to the full analytical and governance lifecycle rather than being limited to routine model processing.

Working closely with colleagues across Risk, Data, Finance and other areas of the Bank, you’ll:

• Analyse portfolio and model data to identify trends, anomalies, unexpected movements and emerging areas of risk.
• Support the monitoring, investigation and ongoing enhancement of the Bank’s IFRS 9 models.
• Gather, validate, reconcile and manipulate data from a range of sources.
• Explore behavioural shifts and help the team understand why model or portfolio performance may be changing.
• Support the development and structured testing of new or amended model components.
• Use tools such as Python, SQL or other analytical languages to investigate data and implement approved changes.
• Produce clear reports, presentations and commentary for both technical and non-technical audiences.
• Maintain accurate documentation covering methodologies, assumptions, testing, limitations and outcomes.
• Help prepare analytical materials for risk and model governance committees.
• Identify opportunities to improve and appropriately automate repeatable monitoring and reporting processes.
• Support audit, assurance and wider governance activity when required.

You’ll bring a logical, curious and methodical approach, with the confidence to investigate results rather than simply accepting them at face value.

In addition, you will have:

• A degree, normally at 2:1 level or above, in a quantitative or analytical subject such as mathematics, statistics, economics, finance, data science, computer science or engineering.
• Academic experience involving mathematics, statistics, quantitative problem-solving or data analysis, potentially demonstrated through a relevant module, project or dissertation.
• Experience of analysing data and translating your findings into clear conclusions or recommendations.
• Strong numerical, analytical and problem-solving skills.
• Some practical exposure to Python, SQL, R or another analytical language, together with the ability and motivation to develop your technical capability.
• Good working knowledge of Microsoft Excel, including organising, reconciling, manipulating and analysing data.
• A structured approach to testing, with the ability to maintain clear evidence of your methods and results.
• The ability to explain analytical information clearly, both verbally and in writing.
• Strong attention to detail and the ability to manage competing priorities

• Experience gained within banking, financial services, credit risk, modelling or another regulated environment.
• An understanding of IFRS 9 models or credit risk principles.
• Experience of model monitoring, model validation or model development.
• Exposure to Databricks or another cloud-based data and analytics platform.
• Experience creating repeatable reports, dashboards or automated analytical processes.
• Confidence using Python or SQL to undertake analytical work.
• Experience preparing analysis for senior stakeholders, governance committees, audit or assurance review.