Credit Risk Modeller
Credit Risk Modeller

Credit Risk Modeller

Full-Time 60000 - 80000 ÂŁ / year (est.) No home office possible
Bits

At a Glance

  • Tasks: Design and implement credit risk models to drive responsible lending practices.
  • Company: Join a mission-driven fintech startup focused on financial inclusion.
  • Benefits: Competitive salary, private health insurance, and flexible hybrid work culture.
  • Why this job: Make a real impact on how people build credit in underserved communities.
  • Qualifications: Strong quantitative skills and experience in credit risk modelling required.
  • Other info: Dynamic environment with opportunities for professional growth and innovation.

The predicted salary is between 60000 - 80000 ÂŁ per year.

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 modeller 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.

Key responsibilities

  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • Research & Innovation: Stay abreast of industry trends, new modelling techniques, and regulatory developments. Recommend enhancements to existing models and explore new approaches.

Qualifications

  • 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 and equity options.
  • Flexible work culture with hybrid setup.

Credit Risk Modeller employer: Bits

At Bits, we pride ourselves on being an exceptional employer, offering a dynamic and inclusive work environment where innovation thrives. As a Credit Risk Modeller, you'll have the opportunity to shape our credit strategy while enjoying professional development, competitive salary, and flexible working arrangements. Join us in making a meaningful impact on financial inclusion and be part of a supportive team at the forefront of fintech.
Bits

Contact Detail:

Bits Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Credit Risk Modeller

✨Tip Number 1

Network like a pro! Reach out to people in the fintech space, especially those working in credit risk. Attend industry events or webinars, and don’t be shy about sliding into DMs on LinkedIn. You never know who might have the inside scoop on job openings!

✨Tip Number 2

Show off your skills! Create a portfolio showcasing your best credit risk models and analyses. Use real-world examples to demonstrate how your work has driven business growth or improved decision-making. This will make you stand out when you apply through our website.

✨Tip Number 3

Prepare for interviews by brushing up on your technical knowledge. Be ready to discuss your experience with statistical methods and machine learning techniques. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with both technical and non-technical stakeholders.

✨Tip Number 4

Stay updated on industry trends! Follow relevant blogs, podcasts, and news sources to keep your knowledge fresh. This will not only help you in interviews but also show potential employers that you're passionate about the field and committed to continuous learning.

We think you need these skills to ace Credit Risk Modeller

Credit Risk Modelling
Statistical Analysis
Machine Learning Techniques
Data Mining
Python for Statistical Modelling
SQL for Data Management
Model Governance
Regulatory Compliance
Communication Skills
Cross-Functional Collaboration
Predictive Modelling
Documentation Best Practices
Trend Analysis
Risk Segmentation
Thought Leadership

Some tips for your application 🫡

Tailor Your CV: Make sure your CV is tailored to the Credit Risk Modeller role. Highlight your experience with credit risk models and any relevant statistical techniques you've used. We want to see how your skills align with our mission at Bits!

Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about democratizing credit and how your background makes you a perfect fit for our team. Let us know what excites you about working in fintech!

Showcase Your Technical Skills: Don’t forget to highlight your technical skills, especially in Python and SQL. We’re looking for someone who can dive into data and extract insights, so make sure we see your proficiency in these areas clearly in your application.

Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right people. We can’t wait to hear from you!

How to prepare for a job interview at Bits

✨Know Your Models Inside Out

Make sure you’re well-versed in the credit risk models you’ve worked on. Be ready to discuss your approach to model development, calibration, and deployment. Highlight specific examples of how your models have driven business decisions or improved outcomes.

✨Data is Your Best Friend

Brush up on your data analysis skills! Be prepared to talk about the statistical techniques you’ve used to extract insights from complex datasets. Show them you can identify trends and risk drivers that enhance model accuracy and predictability.

✨Communicate Like a Pro

You’ll need to explain technical concepts to non-technical stakeholders, so practice simplifying your findings. Think about how you can convey complex ideas clearly and effectively, especially when discussing model governance and regulatory compliance.

✨Stay Ahead of the Curve

Show your passion for innovation by discussing recent trends in credit risk modelling and any new techniques you’re excited about. Mention how you keep up with industry developments and how you’ve applied this knowledge to enhance your work.

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