Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Lead credit risk analytics and develop statistical models for lending strategies.
- Company: Join a dynamic banking sector team focused on credit risk innovation.
- Benefits: Competitive salary, professional development, flexible working, and career progression.
- Why this job: Make a real impact in credit risk while mentoring junior analysts.
- Qualifications: 6-10 years in credit risk analytics with strong Python and SQL skills.
- Other info: Collaborative environment with exposure to international markets.
The predicted salary is between 36000 - 60000 ÂŁ per year.
We are seeking a talented Principal Credit Risk Analyst to join our growing Credit Risk Analytics team. This role is specifically designed for professionals with 6-10 years of experience in the lending industry who are looking to develop their career in credit risk analytics and statistical modelling within the banking sector.
About the Role
As a Principal Credit Risk Analyst, you will contribute to the development, daily management and enhancement of our credit risk analytics capabilities. This is an excellent opportunity for someone with experience in unsecured lending to get wider exposure and larger remit whilst working with cutting‑edge statistical models, data‑driven insights and best‑in‑class datasets. The role focuses on the UK market and requires experience of the UK lending landscape, but you will have the opportunity to work in a pan‑European team and get exposure to credit risk analytics across our international markets including Germany, Austria, Norway, Spain, Italy, and other European markets. The role is ideal for a very experienced analyst who wants to stay hands‑on while developing their mentoring/supervising and DS/analytical product management skills.
Key Responsibilities
- Data Analysis & Insights: Own end‑to‑end strategies for specific population segments. Collect, analyse and interpret data from multiple sources including internal systems, open banking and Credit Reference Agencies (CRAs) to identify trends, patterns and opportunities that inform credit policy, credit limit and pricing strategies.
- Model Development: Develop and maintain statistical models, including scorecards, ML models and other credit risk assessment tools.
- Stakeholder Collaboration: Provide clear, actionable insights and recommendations to stakeholders across the business, supporting informed decision‑making and business growth.
- Cross‑functional Teamwork: Work collaboratively with colleagues in the decision sciences and analytics team, as well as other departments across different locations.
- Communication & Reporting: Present complex analytical findings to both technical and non‑technical audiences through clear presentations, reports and data visualisations.
- Mentoring: Mentor and supervise junior analysts on model and strategy development projects, and Python model pipeline development.
Essential Requirements
- Education & Experience: Bachelor degree in Mathematics, Statistics, Economics, Physics, Computer Science, Engineering or related quantitative discipline from a well‑regarded university. 6-10 years of experience in analytics, data analysis or lending/credit assessment within the financial services sector. Previous experience working for an unsecured lender, preferably on Credit Card products.
- Technical Skills: Strong analytical and problem‑solving abilities with excellent attention to detail. Proficiency in SQL for data extraction, manipulation and analysis. Strong programming experience in Python (ideally for model development). Understanding of statistical analysis techniques and data modelling methodologies. Experience in predictive modelling (logistic regression and GBM knowledge at minimum). Understanding of machine learning techniques applied to credit risk.
- Professional Skills: Excellent written and verbal communication skills in English. Ability to translate complex data into clear, actionable business insights. Strong presentation skills with experience communicating to diverse audiences. Proven ability to work effectively in fast‑paced environments whilst managing multiple priorities. Team player.
Desirable Requirements
- Postgraduate qualification in a relevant quantitative field.
- Knowledge of credit risk regulations and best practices in the UK market.
- Experience with data visualisation tools.
- Experience of full credit card customer journey (from origination to recoveries).
- Experience with model pipeline maintenance.
- Experience with model monitoring.
- Experience in analytics/DS project management.
What We Offer
- Competitive salary and benefits package.
- Opportunity to work with advanced analytics and statistical modelling techniques.
- Professional development and training opportunities.
- Collaborative, inclusive working environment.
- Flexible working arrangements.
- Career progression opportunities within our growing analytics function.
Application Requirements
Please note: We are unable to provide visa sponsorship for this role. Candidates must have the right to work in the UK without requiring sponsorship. We are committed to creating an inclusive workplace that reflects the diversity of the communities we serve. We welcome applications from all qualified candidates regardless of age, disability, gender identity, race, religion, sexual orientation or background.
Department: Risk & Decision Analytics
Locations: London
Remote status: Hybrid
Employment type: Full-time
Principal Credit Risk Analyst employer: TF Bank
Contact Detail:
TF Bank Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Principal Credit Risk Analyst
✨Network Like a Pro
Get out there and connect with folks in the credit risk and analytics space! Attend industry events, webinars, or even local meetups. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Show Off Your Skills
When you land that interview, be ready to showcase your analytical prowess. Bring examples of your work, like models you've developed or insights you've generated. This is your chance to shine and demonstrate how you can add value to the team!
✨Tailor Your Approach
Make sure to tailor your discussions to the specific role of Principal Credit Risk Analyst. Highlight your experience in unsecured lending and your familiarity with the UK market. This shows you're not just any analyst; you're the right fit for this position!
✨Apply Through Us!
Don't forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team. Plus, it gives us a chance to see your application in the best light possible.
We think you need these skills to ace Principal Credit Risk Analyst
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in credit risk analytics and statistical modelling. We want to see how your skills align with the role, so don’t be shy about showcasing your relevant projects and achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about credit risk and how your background makes you a perfect fit for our team. Keep it concise but impactful – we love a good story!
Show Off Your Technical Skills: Since this role requires strong analytical abilities, make sure to mention your proficiency in SQL and Python. If you’ve worked on predictive modelling or machine learning techniques, let us know – we’re keen to hear about your hands-on experience!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re serious about joining our awesome team at StudySmarter!
How to prepare for a job interview at TF Bank
✨Know Your Numbers
As a Principal Credit Risk Analyst, you'll need to demonstrate your analytical prowess. Brush up on key metrics and statistical models relevant to credit risk assessment. Be ready to discuss how you've used data to drive decisions in previous roles.
✨Showcase Your Technical Skills
Make sure you highlight your proficiency in SQL and Python during the interview. Prepare examples of how you've developed or maintained statistical models, and be ready to explain your approach to predictive modelling and machine learning techniques.
✨Communicate Clearly
You’ll need to present complex findings to both technical and non-technical audiences. Practice explaining your past projects in simple terms, focusing on the insights gained and their impact on business strategies. Clear communication is key!
✨Be a Team Player
Collaboration is crucial in this role. Share examples of how you've worked with cross-functional teams in the past. Highlight your mentoring experience and how you've supported junior analysts, as this will show your leadership potential.
