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.
We asked employees of Atom Bank how satisfied they were with flexible working, and this is what they told us
Working at Atom Bank
Gender diversity (male:female)
Durham & London