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- Tasks: Lead the development of behavioural credit models to enhance credit decisions.
- Company: Join a UK-based fintech reshaping consumer finance with ethics and accountability.
- Benefits: Enjoy flexible hybrid working, competitive salary, and generous holiday allowance.
- Why this job: Make a real-world impact in a fast-paced, data-driven environment with a collaborative team.
- Qualifications: Bachelor's in Computer Science or related field; advanced SQL and Python skills required.
- Other info: No VISA sponsorship available; ideal for those passionate about data and credit modelling.
The predicted salary is between 60000 - 84000 £ per year.
Job Description
Senior Data Scientist – Behavioural Credit Modelling
Hybrid working – London offices
Up to £75,000 DOE + Benefits
Ref: J12979
Are you passionate about building behavioural models that power smarter, fairer credit decisions?
We’re working with a UK-based consumer finance specialist that’s reshaping the credit industry, cutting out complexity and using data to drive real-world impact. Think Challenger Fintech for consumer finance, with clear ethics and accountability.
This is a genuine opportunity to make your mark in a high-growth business that’s reshaping credit from the inside out.
About the Role
As a Senior Data Scientist, you’ll take ownership across the full lifecycle of model development—from data wrangling and feature engineering to building and deploying ML models in production.
Your work will directly power business decisions across underwriting, fraud detection, and customer conversion. This is a hands-on, end-to-end role where your skills in predictive modelling will make a real-world impact.
You’ll be working with structured and unstructured data as part of a collaborative, agile team—developing intelligent solutions that support fair and effective credit decisions.
We’re looking for someone who:
- Has a Bachelor’s degree in Computer Science, Mathematics, Statistics, or related field
- Brings advanced SQL skills and strong experience with Python (pandas, sklearn, seaborn, etc.)
- Understands the mechanics behind ML algorithms—not just how to run them
- Enjoys solving problems and improving processes
- Has hands-on experience developing underwriting or behavioural credit models – Expect to be using your skills to design, build, and deploy models from day one
- Communicates effectively with both technical and non-technical stakeholders
- Thrives in a fast-moving, data-led environment
- Understands the importance of monitoring for data drift
- Visualisation is a key aspect of the role — Be ready to bring your team's ideas to life!
It’s a plus if you also have:
- A Master’s in Data Science, ML, or a related field
- Credit card industry knowledge
- Experience with deep learning (Keras, TensorFlow)
- Familiarity with GitHub or Bitbucket
- Tableau experience or similar
- An interest in applying research to commercial problems
- Knowledge of the credit card or consumer finance sector
What’s in it for you?
- Competitive salary, benchmarked against the industry
- Flexible hybrid working (London office)
- Annual bonus scheme
- Enhanced pension contribution options
- 25–30 days holiday + your birthday off
- Private medical cover (Vitality)
- Enhanced family-friendly policies
- Employee Assistance Programme
- Great culture, perks, and recognition schemes
No VISA sponsorship is being offered for this role.
Senior Data Scientist Behavioural Credit Modelling employer: Datatech Analytics
Contact Detail:
Datatech Analytics Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist Behavioural Credit Modelling
✨Tip Number 1
Network with professionals in the fintech and credit modelling space. Attend industry meetups or webinars to connect with potential colleagues and learn about the latest trends. This can help you gain insights into what the company values and may even lead to a referral.
✨Tip Number 2
Showcase your hands-on experience with behavioural credit models by discussing relevant projects during interviews. Be prepared to explain your approach to model development, including data wrangling and feature engineering, as this will demonstrate your practical skills.
✨Tip Number 3
Familiarise yourself with the company's mission and values, especially their focus on ethical credit decisions. Tailor your discussions to reflect how your personal values align with theirs, which can make a strong impression during interviews.
✨Tip Number 4
Prepare to discuss your experience with visualisation tools like Tableau. Being able to effectively communicate complex data insights is crucial for this role, so having examples ready can set you apart from other candidates.
We think you need these skills to ace Senior Data Scientist Behavioural Credit Modelling
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data science, particularly in behavioural credit modelling. Emphasise your skills in SQL and Python, and include specific projects or achievements that demonstrate your ability to develop and deploy ML models.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for the role and the company. Discuss how your background aligns with their mission of reshaping the credit industry and mention any specific experiences that relate to the job description.
Showcase Your Technical Skills: In your application, be sure to detail your technical skills, especially in predictive modelling and data visualisation. Mention any experience you have with tools like Keras, TensorFlow, or Tableau, as well as your understanding of ML algorithms.
Prepare for Potential Questions: Anticipate questions related to your experience with model development and problem-solving in a data-led environment. Be ready to discuss how you've handled data drift and your approach to communicating complex ideas to non-technical stakeholders.
How to prepare for a job interview at Datatech Analytics
✨Showcase Your Technical Skills
Be prepared to discuss your advanced SQL and Python skills in detail. Bring examples of past projects where you used libraries like pandas, sklearn, or seaborn to solve real-world problems, especially in behavioural credit modelling.
✨Understand the Business Impact
Demonstrate your understanding of how your work as a data scientist can influence business decisions. Be ready to explain how your models can improve underwriting processes, fraud detection, and customer conversion rates.
✨Communicate Clearly
Since you'll be working with both technical and non-technical stakeholders, practice explaining complex concepts in simple terms. Prepare to discuss how you would present your findings and visualisations effectively.
✨Prepare for Problem-Solving Questions
Expect to face questions that assess your problem-solving abilities. Think of scenarios where you've had to improve processes or tackle challenges in model development, and be ready to share your thought process.
