Lead Credit Risk Modeller

Job Description

What’s it all about?

Insight and Intelligence drives Atom.

The Insight & Intelligence team leverage Big Data tech, to maximise the returns from our data assets, by providing MI, exploratory analysis & predictive models. These shape & deliver strategies in pricing, direct marketing, product optimisation, credit risk & fraud.

Here at Atom we are embarking on an exciting programme of work, to achieve an A-IRB Waiver by FY25. As Lead IRB Credit Risk Modeller you will primarily focus on developing and implementing various types of predictive models, segmentation strategies, optimisation algorithms & data mining analysis. You’ll also aid the development, maintenance and monitoring of new IRB rating systems, regulatory PD, LGD, EAD & scorecard models.

In this role you will support initiatives in the regulatory & compliance space within risk such as IRB, forecasting & stress testing. You’ll also provide support and guidance to a team of Credit Risk Modellers, providing oversight to the work they produce.

IRB knowledge and experience is essential for this role.

What will your ‘typical’ day look like…. (there’s no 2 days the same in Atom):

• Assessment of IRB regulation within the CRR, SS11/13, EBA GL’s, PRA Rulebook & Basel 3.1 for residential mortgages or business loans
• Developing and implementing various types of predictive models, segmentation strategies, optimisation algorithms and data mining analysis
• Monitor and maintaining models to ensure that they remain fit for purpose
• Develop and implementing various types of predictive models, segmentation strategies, optimisation algorithms and data mining analysis to drive pricing and liquidity management
• Ensure predictive models support regulatory and compliance initiatives within risk such application scorecards, capital and impairment (according to IRB and IFRS9 standards) and stress testing
• Create simulation models to help optimise operational processes and quantify and manage operational risks.

What do we need from you?

• Experience with IRB regulation (CRR, SS11/13, EBA GL’s, PRA Rulebook & Basel 3.1)
• Experience in using the following modelling techniques – collaborative filtering, support vector machines, neural networks, linear and logistic regression, decision trees, random forests
• Experience of data analysis tools, such as SQL, R, Python, SAS or similar
• Good communication skills - able to present analysis at all levels of the business and to non-specialists
• A self-starter with excellence time management skills
• Experience of delivering predictive models to support application or behavioural credit risk scoring, IRB, IFRS9, scorecards, pricing and price elasticity, or product propensity models.