Ventula Consulting
Credit Risk modeler (Scorecards)
Get notified of more jobs like this · No spam, ever
How your CV stacks up
Upload your CV to see how well it fits this job role
?%
Credit Risk Modeler
Global Financial Services Client now require a Credit Risk Modeler to join a high-performing Product Analytics & Innovation team building market-leading credit risk scores, predictive models, and AI-driven commercial data products on modern cloud infrastructure.
Core Objective
Independently build a point-of-application risk scorecard from scratch within a tight window. The ideal candidate must take raw, uncleaned data and deliver a fully validated, production-ready logistic regression model.
Hands-on Scorecard Build History
Must have personally built and deployed at least 2 end-to-end credit scorecards (consumer or commercial). We are looking for someone who writes the code and build the bins rather than a manager or analyst who only reviews the output.
Hands-On Python Execution
Advanced, fluent Python coder. Must be comfortable writing custom data transformation functions and debugging logic live without relying on template scripts or AI coders.
Pragmatic Data Engineering
Strong SQL skills to ingest, merge, and clean messy, high-dimensional datasets independently in cloud environments (GCP/BigQuery preferred).
Reasons to use Rodeo
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
It searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
The Data Scientist will:
- Independently prepare complex datasets, run exploratory analysis, and build predictive models, risk scorecards, and decisioning tools
- Drive commercial product innovation — identify market gaps, prototype algorithms, take concepts to market-ready products
- Design and optimise data pipelines integrating large volumes of disparate commercial data
- Translate data assets into actionable business strategy and long-term analytics roadmap
- Apply advanced statistical/ML methods to uncover patterns in high-dimensional data
- Solve cross-domain problems (commercial risk, business failure, fraud detection) with engineering, product, and strategy teams
- Communicate complex findings clearly to technical and non-technical stakeholders
- Maintain data quality, governance, validation, and regulatory compliance standards
- Stay current with cloud capabilities (primarily GCP) and modern analytical tooling
- Mentor junior data scientists and lead code/quality reviews
The ideal Data Scientist will have the following experience:
Get help with your application
Your very own career expert that helps elevate your application to the next level.
- STEM degree (Master's preferred)
- Proven experience working in a Data Scientist or quantitative modeling role
- Extensive experience with commercial data assets (e.g. business registry, trade credit, or bureau data)
- Strong commercial data interpretation, auditing, and validation skills
- Python and SQL (Unix/shell scripting a plus)
- Foundational credit risk modeling / scorecard lifecycle knowledge (sampling, WoE, scaling)
- Git and CI/CD workflow experience
- Hands-on cloud development experience (GCP preferred)
- Exposure to ML methods (XGBoost, Random Forests, Neural Networks) and traditional stats (Logistic Regression)
- Awareness of data security, governance, and model risk management standards
Nice to Have
- UK commercial lending/regulatory knowledge (PRA/FCA, Consumer Duty, Basel 3.1)
- Experience building/validating commercial credit scorecards
- Exposure to Open Banking, transactional data, bureau feeds, ESG data
- Track record of independently pitching and delivering analytical products
Rate
£700p/d Inside IR35
Location
London (hybrid)
Duration
6 months rolling
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
Skills
Location