WHAT WE’RE LOOKING FOR:

We’re looking for someone with a passion for data-driven decisioning and a track record of delivering credit risk models in a regulated environment. You should enjoy combining technical excellence with commercial thinking and collaboration.

ESSENTIAL SKILLS AND EXPERIENCE:

• Proven experience developing credit scorecards or other classification models within financial services.
• Strong programming ability in SAS or Python; familiarity with libraries such as NumPy, Pandas, Scikit-learn, Keras, and Matplotlib is a plus.
• Working knowledge of algorithms such as logistic regression, tree-based methods (e.g. random forests, gradient boosting), and neural networks.
• Proficiency in SQL and experience with data extraction, manipulation, and analysis from relational databases.
• Solid understanding of statistical methods, experiment design, and hypothesis testing.
• Familiarity with Credit Reference Agency data, characteristics, and score usage.
• A structured, analytical mindset and problem-solving capability.

WHO WE ARE:

At Vanquis, we have a simple purpose: to deliver caring banking so our customers can make the most of life’s opportunities. Established in 1880, we’re now a FTSE All Share company and leading specialist bank. We lend responsibly, providing tailored products and services to over 1.75 million UK customers.
We take care of our colleagues as well as our customers, working hard to create a rewarding and supportive work environment. That means competitive salaries, benefits, and a Group-wide recognition scheme. Everyone can enrol in our pension and after six months, you can join our ‘Buy as You Earn’ scheme.
We’re about more than financial rewards though. We give everyone a voice in the business and room to be their authentic self. And we know you’re here to build your career, so we help every colleague with training and development opportunities. Making sure there’s always something new to learn.

SOME OF THE KEY RESPONSIBILITIES ARE:

• Developing Acquisition and Behavioural Scorecards across Cards and Asset Finance portfolios.
• Designing and enhancing IFRS9 and Capital Models, including ECL and PD modelling.
• Creating, maintaining, and automating model monitoring and performance dashboards.
• Building development datasets from internal and external data sources, including Credit Reference Agencies.
• Applying segmentation techniques to identify homogenous populations for targeted modelling.
• Collaborating cross-functionally with teams such as Product, Finance, Credit Risk, and Operations to embed analytics into strategic decision-making.
• Mentoring junior analysts, supporting skill development and contributing to a culture of continuous improvement.