Credit Risk Manager

TF Bank
London
10 months ago
Applications closed

Related Jobs

View all jobs

Credit Risk Manager (Data Scientist)

Senior Data Scientist

Manager - Data and Data Science Strategy - Emerging Data and Capabilities

Senior Data Scientist - Home Insurance

Senior Data Scientist - Home Insurance

CareerStart@SAS 2026 - Customer Facing Intern – AI, Data Science & Risk Management

As aCredit Risk Manageryou will develop datadriven strategies analyse trends and optimize credit policies for credit cards. Collaborating with teams across Europe youll provide insights to drive business growth and foster innovation in credit risk management.


Key responsibilities:

  • Be a handson expert in credit risk area.
  • Collect and analyze data from various sources including internal systems Credit Bureaus to identify trends patterns and opportunities.
  • Analyse and make recommendations that help the development of credit policy scorecards and limit management strategies for credit cards.
  • Provide actionable insights and recommendations to stakeholders based on data analysis helping them make informed decisions and drive business growth.
  • Foster a culture of datadriven decision making within the organization promoting the use of analytics to drive continuous improvement and innovation.
  • Collaborate with other analytical teams across the European organization.


Qualifications and previous experience:

  • Master degree in a relevant field such as Mathematics Statistics Economics Quantitative Methods Computer Science or Engineering.
  • Minimum of 5 years of experience in analytics or a data science field.
  • Practical knowledge of the British credit card market and Credit Bureaus.
  • Experience in consumer finance credit risk area in banks or fintechs.
  • Deep understanding of credit card products including risk and profitability drivers.
  • Excellent analytical and problemsolving skills with a strong attention to detail. Algorithmic and creative approach to solving problems.
  • Proven track record of delivering impactful insights and recommendations based on data analysis.


Skills:

  • Proficiency in data modelling methodologies and statistical analysis techniques.
  • Excellent knowledge of SQL for data extraction and manipulation.
  • Experience in predictive modelling using logistic regression is required.
  • Knowledge of programming languages such as Python or R will be a plus.
  • Fluent English to be able to collaborate with colleagues from other countries.
  • Good communication and presentation skills with the ability to translate complex data into clear and actionable insights.
  • Ability to work effectively in a fastpaced dynamic environment managing multiple priorities and meeting deadlines.


Location:London


Key Skills
Arm,Risk Management,Financial Services,Cybersecurity,COSO,PCI,Root cause Analysis,COBIT,NIST Standards,SOX,Information Security,RMF
Employment Type :Full Time
Experience:years
Vacancy:1

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Neurodiversity in AI Careers: Turning Different Thinking into a Superpower

The AI industry moves quickly, breaks rules & rewards people who see the world differently. That makes it a natural home for many neurodivergent people – including those with ADHD, autism & dyslexia. If you’re neurodivergent & considering a career in artificial intelligence, you might have been told your brain is “too much”, “too scattered” or “too different” for a technical field. In reality, many of the strengths that come with ADHD, autism & dyslexia map beautifully onto AI work – from spotting patterns in data to creative problem-solving & deep focus. This guide is written for AI job seekers in the UK. We’ll explore: What neurodiversity means in an AI context How ADHD, autism & dyslexia strengths match specific AI roles Practical workplace adjustments you can ask for under UK law How to talk about your neurodivergence during applications & interviews By the end, you’ll have a clearer picture of where you might thrive in AI – & how to set yourself up for success.

AI Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we head into 2026, the AI hiring market in the UK is going through one of its biggest shake-ups yet. Economic conditions are still tight, some employers are cutting headcount, & AI itself is automating whole chunks of work. At the same time, demand for strong AI talent is still rising, salaries for in-demand skills remain high, & new roles are emerging around AI safety, governance & automation. Whether you are an AI job seeker planning your next move or a recruiter trying to build teams in a volatile market, understanding the key AI hiring trends for 2026 will help you stay ahead. This guide breaks down the most important trends to watch, what they mean in practice, & how to adapt – with practical actions for both candidates & hiring teams.

How to Write an AI CV that Beats ATS (UK examples)

Writing an AI CV for the UK market is about clarity, credibility, and alignment. Recruiters spend seconds scanning the top third of your CV, while Applicant Tracking Systems (ATS) check for relevant skills & recent impact. Your goal is to make both happy without gimmicks: plain structure, sharp evidence, and links that prove you can ship to production. This guide shows you exactly how to do that. You’ll get a clean CV anatomy, a phrase bank for measurable bullets, GitHub & portfolio tips, and three copy-ready UK examples (junior, mid, research). Paste the structure, replace the details, and tailor to each job ad.