Senior Analyst - Decision Science
Role details
Job location
Tech stack
Job description
As a Senior Analyst - Decision Science, you will play a key role in delivering innovative, accurate, and scalable models that underpin our collections and fraud strategies that support sustainable customer outcomes.
You and your Team
The Data & Analytics function is a centre of excellence that provides high-impact analytical expertise across the Vanquis Banking Group. We're responsible for business-critical modelling, data innovation, credit bureau strategy, and actionable insights that drive customer and commercial outcomes.
This new role will sit in our Decision Science team. The wider team focuses on developing robust, regulatory-aligned models and decisioning tools, and you will be specifically involved in developing and maintaining predictive models that enhance collections strategies and fraud detection frameworks.
As a Senior Analyst, you will:
- Developing predictive models for collections optimisation and fraud detection across Cards and Asset Finance portfolios.
- Assess customer behaviours, repayment patterns, and fraud trends, identifying opportunities to improve collections strategies and fraud prevention measures.
- 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.
Requirements
Do you have experience in SQL?, We're looking for someone with a passion for dynamic problem solving and a track record of delivering predictive models in financial services. You should enjoy combining technical excellence with commercial thinking and collaboration., * 2+ years' experience developing credit scorecards or other classification models (within financial services is a plus).
- Strong programming ability in either Python or SQL; familiarity with libraries such as NumPy, Pandas, Scikit-learn, Keras, and Matplotlib.
- Familiarity with algorithms such as logistic regression and tree-based methods (e.g. random forests, gradient boosting).
- Familiarity with Credit Reference Agency data, characteristics, and score usage.
- A structured, analytical mindset and problem-solving capability.
Desirable skills:
- Exposure to cloud-based analytics environments.
- Experience with machine learning techniques for fraud detection.
Offers are subject to standard background checks (credit, fraud and employment references).
Benefits & conditions
Working Pattern: Hybrid (usually a couple of days a week in the office).
We welcome part-time and flexible arrangements and will aim to match your current flexibility where possible.
What We Offer
We care about your wellbeing, not just your work. Our benefits are designed to support your life, your health and your growth:
- Holidays: 25 days (rising to 30) + buy/sell up to 5 days + swap up to 4 bank holidays.
- Pension: Up to 10% employer contribution.
- Enhanced Leave: Enhanced maternity (post-probation), 4 weeks' paternity, and paid neonatal & carers leave.
- Workations: Work abroad for up to 20 days a year in approved countries.
- Birthday Leave: Your birthday off-paid.
- Volunteering: 2 paid volunteering days.
- Learning: Access to LinkedIn Learning for all colleagues.
- Financial Wellbeing: Free Snoop Premium subscription.
- Healthcare: Self-pay Denplan & optional Private Medical Insurance.
