Risk Analytics - Model Development

About OakNorth Bank

Since our launch in 2015, we’ve backed entrepreneurs with over £13bn in funding, helping create 56,000+ jobs and 34,000+ new homes across the UK and US. We are dedicated to helping trailblazing businesses thrive, and our strong analytics capabilities help us build trust and secure our digital assets and customer data.

This is a fantastic opportunity to join a fast-paced, growing bank with a reputation for doing things differently. We don’t want another cog in the machine; we’re looking for self-starters and bold thinkers who want to pave their own career.

In this exciting role within the Risk Analytics team, you will be responsible for statistical model development, validation, and monitoring of credit risk models – PD/LGD/EAD, ECL, and ICAAP models – and solving business problems leveraging quantitative tools and techniques. You will also be involved in provisioning and stress testing exercises for the bank.

Responsibilities

• Developing, validating, monitoring, and implementing credit risk models – PD /LGD /EAD /IFRS9 /Stress Testing – for the bank, considering both qualitative and quantitative factors; and analysing, explaining, and documenting models and results in detail.
• Carrying out other analysis such as periodic provisioning and stress testing exercises.
• Researching and suggesting quantitative and qualitative techniques for model enhancements.
• Building and enhancing governance framework as per regulatory requirements.
• Coding in R/Python to develop and enhance models, perform analysis, and automate processes.
• Liaising with multiple teams and various business units across the bank for different risk management activities.
• Communicating with stakeholders, internal audit, model validation, and other parties, and responding to their requests timely and accurately.

Required Experience

• 3-6 years of relevant experience at a financial institution or a consulting firm, preferably in a Quant/Data Science role in a data-rich environment.
• Preferably Master’s degree in a quantitative field such as Statistics, Mathematics, Operations Research, Economics, or Finance, or equivalent.
• Experienced in developing/validating credit risk models.
• Experienced in provisioning as per IFRS9 implementation for banks.
• Understanding of risk management concepts like Stress testing, regulatory frameworks for banks.
• Proficiency in programming and Advanced Statistical Techniques – R/Python/Advanced Excel.
• Analytical thinking, quantitative abilities, and problem-solving skills.
• Attention to detail.
• Ability to work well under pressure in a fast-paced team-oriented environment.
• Strong communication skills; ability to present complex and technical issues clearly, both verbally and in writing.
• FRM/CFA certification or equivalent is a plus.

Key skills/competency

• Credit Risk Modeling
• PD/LGD/EAD
• IFRS9
• Stress Testing
• Quantitative Analysis
• R Programming
• Python Programming
• Statistical Modeling
• Regulatory Compliance
• Financial Risk Management