Risk Analytics - Model Development (Python)

ONGPL Risk Analytics /Permanent - Full Time /On-site

Since our launch in 2015, weve backed entrepreneurs with over 13bn in funding, helping create 56,000+ jobs and 34,000+ new homes across the UK and US and were not about to stop there. Were 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 dont want another cog in the machine, were looking for self-starters and bold thinkers who want to pave their own career.

In a nutshell, in this exciting role in 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 of 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 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:

• 2-6 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 Masters 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

About Us

Were OakNorth Bank and we embolden entrepreneurs to realise their ambitions, understand their markets, and apply data intelligence to everyday decisions to scale successfully at pace.

Banking should be barrier-free. Its a belief at our very core, inspired by our entrepreneurial spirit, driven by the unmet financial needs of millions, and delivered by our data-driven tools.

And for those who love helping businesses thrive? Our savings accounts help diversify the high street and create new jobs, all while earning savers some of the highest interest on the market.

But we go beyond finance, to empower our people, encourage professional growth and create an environment where everyone can thrive. We strive to create an inclusive and diverse workplace where people can be themselves and succeed.

Our story

OakNorth Bank was built on the foundations of frustrations with old-school banking. In 2005, when our founders tried to get capital for their data analytics company, the computer said no. Unfortunately, all major banks in the UK were using the same computer and it was broken.

Why was it so difficult for a profitable business with impressive cashflow, retained clients, and clear commercial success to get a loan?

The industry was backward-looking and too focused on historic financials, rather than future potential.

So, what if there was a bank, founded by entrepreneurs, for entrepreneurs? One that offered a dramatically better borrowing experience for businesses?

No more what ifs, OakNorth Bank exists.

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