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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 a relevant field, advanced SQL, Python skills, and experience in credit modelling required.
- Other info: No VISA sponsorship available; ideal for those passionate about data and finance.
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
Familiarise yourself with the latest trends in behavioural credit modelling. Understanding current methodologies and technologies will not only enhance your knowledge but also demonstrate your passion for the field during discussions.
✨Tip Number 2
Network with professionals in the fintech and credit sectors. Attend industry meetups or webinars to connect with potential colleagues or mentors who can provide insights into the company culture and expectations.
✨Tip Number 3
Prepare to discuss your hands-on experience with model development. Be ready to share specific examples of projects where you’ve successfully built and deployed models, as this will showcase your practical skills and problem-solving abilities.
✨Tip Number 4
Brush up on your communication skills, especially when it comes to explaining complex data concepts to non-technical stakeholders. Being able to convey your ideas clearly will set you apart in a collaborative environment.
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 any hands-on experience with model development.
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 to reshape the credit industry and mention specific projects or achievements that demonstrate your expertise.
Showcase Technical Skills: In your application, clearly outline your technical skills, especially in predictive modelling and machine learning algorithms. Provide examples of how you've used these skills in previous roles to solve problems or improve processes.
Prepare for Potential Questions: Anticipate questions related to your experience with data wrangling, feature engineering, and model deployment. Be ready to discuss how you communicate complex ideas to both technical and 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've used libraries like pandas, sklearn, or seaborn to solve real-world problems, especially in the context of 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 Effectively
Practice explaining complex technical concepts in simple terms. You’ll need to communicate with both technical and non-technical stakeholders, so being able to bridge that gap is crucial.
✨Prepare for Problem-Solving Questions
Expect to face questions that assess your problem-solving abilities. Think about challenges you've encountered in previous roles and how you overcame them, particularly in developing and deploying ML models.
