Credit Risk Modeler

London, England, United Kingdom

Bits

Build Credit with Experian, Equifax and TransUnion. No interest, no late fees, and no hard credit check.

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About Bits:

At Bits, we’re on a mission to democratize credit and build a fairer financial future. We help customers across the UK and beyond to build their credit profile through smart, responsible financial tools. As we scale our operations and launch new products, we’re expanding our Risk element with a key technical hire who will shape the future of our credit strategy and help us manage risk intelligently.

About the Role:

We are looking for a skilled and analytical Credit Risk Modeler to join our growing team. In this role, you will design, implement, and maintain robust credit risk models that are critical to Bits’ decision-making framework. You’ll play a central role in model governance, regulatory compliance, and translating complex data into actionable business insights.

This is a high-impact role for someone with a deep understanding of credit risk, strong quantitative skills, and a passion for driving responsible lending practices in a fast-paced fintech environment.

1. Model Development and Implementation

  • Develop, calibrate, and deploy credit risk models across the customer lifecycle, with a focus on acquisition and behavioural models such as application scorecards, early warning signals, and delinquency / default prediction models - using advanced statistical and machine learning techniques.
  • Lead end-to-end model lifecycle from initial data exploration to production deployment.

2. Data Analysis and Interpretation

  • Apply advanced statistical and data mining techniques to extract meaningful insights from large and complex datasets.
  • Identify trends and risk drivers to inform and improve model accuracy and predictability.

3. Credit Strategy & Portfolio Growth

  • Play a key role in leveraging these models to shape data-driven credit strategies that drive business growth, improve customer retention, and optimise revenue across the portfolio.

4. Monitoring and Maintenance

  • Regularly monitor model performance and recalibrate as necessary to reflect portfolio and macroeconomic changes.
  • Maintain thorough documentation and version control for all models.

5. Stakeholder Communication

  • Communicate technical findings clearly to both technical and non-technical stakeholders, including senior leadership and regulatory bodies.
  • Provide thought leadership on model risk and credit strategy.

6. Cross-Functional Collaboration

  • Work closely with other departments - Product, Engineering, and Compliance teams to ensure models are integrated effectively into decision engines and business processes.

7. Research & Innovation

  • Stay abreast of industry trends, new modeling techniques, and regulatory developments.
  • Recommend enhancements to existing models and explore new approaches.

Requirements

  • Strong academic background in a quantitative field (e.g., Mathematics, Statistics, Engineering, Computer Science).
  • 5+ years of experience building and validating credit risk models in a financial services or fintech environment.
  • Proficiency in both traditional statistical methods (e.g. logistic regression) and modern machine learning approaches (e.g. XGBoost, random forests) for predictive modeling and risk segmentation.
  • Proficiency in Python for statistical modeling and data analysis.
  • Strong SQL skills and experience working with large datasets.
  • Proven ability to work with credit bureau and open banking data to design predictive models and shape data-driven acquisition and customer management strategies.
  • Experience with regulatory frameworks such as Basel and IFRS 9 is a plus, particularly in the context of credit risk modeling.
  • Excellent written and verbal communication skills with the ability to influence stakeholders at all levels.
  • Familiarity with model governance, validation, and documentation best practices.

Benefits

  • A dynamic and inclusive work environment in a rapidly growing fintech startup.
  • Opportunities for professional development and career growth.
  • The chance to make a significant impact on financial inclusion and credit building for underserved communities.
  • Make an impact in a mission-led company redefining how people build credit.
  • Work with a smart, supportive, and driven team at the cutting edge of fintech.
  • Private health insurance, L&D budget, and other great perks.
  • Competitive salary.
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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

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Tags: Banking Computer Science Credit risk Data analysis Data Mining Engineering FinTech Machine Learning Mathematics ML models Predictive modeling Python Research SQL Statistical modeling Statistics XGBoost

Perks/benefits: Career development Competitive pay Health care Startup environment

Region: Europe
Country: United Kingdom

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