Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Lead client projects and engage in quantitative risk assessments.
- Company: Join a dynamic team focused on Credit Risk in a leading financial services firm.
- Benefits: Enjoy competitive pay, flexible working options, and opportunities for professional growth.
- Why this job: Make an impact in the financial sector while developing cutting-edge AI solutions.
- Qualifications: Bachelor's degree in relevant fields and experience in Financial Services required.
- Other info: Ideal for those passionate about data science and credit risk management.
The predicted salary is between 48000 - 72000 £ per year.
Our client is looking for a Credit Data Scientist (Manager) to join the Credit Risk team within their London office. The Manager will lead client engagements and internal projects and take the lead in identifying and developing potential business opportunities on existing engagements.
As a Manager you will be involved in the following activities:
- Participating in quantitative risk engagements, primarily along the credit life cycle
- Working effectively as a team member sharing responsibility, providing support, maintaining communication, and updating senior team members on progress
- Assisting in the preparation of reports and schedules
- Developing and maintaining productive working relationships with clients
- Contributing and driving the development of different aspects of the Trusted AI solution
- Conducting performance reviews and contributing to performance feedback for staff
To qualify for the role you must have:
- Experience in Financial Services, either as part of an institution, or as a regulator of such institutions
- Strong academic background including at least a Bachelor's degree (Computational Finance, Mathematics, Engineering, Statistics, or Physics preferred) or equivalent
- Knowledge of Probability of Default (PD) / Loss Given Default (LGD) / Exposure at Default (EAD) / Internal Ratings Based (IRB) / Stress Testing
- Knowledge of Credit Risk and Financial Services Regulation
- Experience in any of the following software development environments: Python / R / SAS / SQL / Matlab
- Knowledge of standard Machine Learning techniques, and their potential applications
- Strong analytical problem-solving skills
- Project management and excellent report writing skills
- Experience in stakeholder and client management
Credit Data Scientist - Manager employer: Campion Pickworth
Contact Detail:
Campion Pickworth Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Credit Data Scientist - Manager
✨Tip Number 1
Network with professionals in the financial services sector, especially those who work in credit risk. Attend industry events or webinars to connect with potential colleagues and learn about the latest trends in credit data science.
✨Tip Number 2
Familiarise yourself with the specific software tools mentioned in the job description, such as Python, R, and SQL. Consider taking online courses or working on personal projects that showcase your skills in these areas.
✨Tip Number 3
Prepare to discuss your experience with quantitative risk engagements during interviews. Be ready to provide examples of how you've contributed to projects involving Probability of Default (PD) or Loss Given Default (LGD).
✨Tip Number 4
Demonstrate your project management skills by discussing past experiences where you led a team or managed client relationships. Highlight your ability to communicate effectively and keep stakeholders informed throughout the project lifecycle.
We think you need these skills to ace Credit Data Scientist - Manager
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in Financial Services and showcases your strong academic background. Emphasise your knowledge of credit risk concepts like PD, LGD, and EAD, as well as your proficiency in software development environments such as Python or R.
Craft a Compelling Cover Letter: Write a cover letter that clearly outlines your motivation for applying to the Credit Data Scientist position. Discuss how your skills and experiences align with the responsibilities mentioned in the job description, particularly your project management and report writing skills.
Showcase Analytical Skills: In your application, provide specific examples of how you've used analytical problem-solving skills in past roles. Highlight any projects where you contributed to quantitative risk engagements or developed machine learning solutions.
Highlight Stakeholder Management Experience: Demonstrate your experience in stakeholder and client management by including examples of how you've built productive working relationships in previous positions. This will show your ability to lead client engagements effectively.
How to prepare for a job interview at Campion Pickworth
✨Showcase Your Technical Skills
As a Credit Data Scientist, you'll need to demonstrate your proficiency in software development environments like Python, R, or SQL. Be prepared to discuss specific projects where you've applied these skills, and consider bringing examples of your work to the interview.
✨Understand Credit Risk Fundamentals
Make sure you have a solid grasp of key concepts such as Probability of Default (PD), Loss Given Default (LGD), and Internal Ratings Based (IRB). Being able to explain these terms clearly will show your expertise and understanding of the credit life cycle.
✨Prepare for Scenario-Based Questions
Expect questions that assess your analytical problem-solving skills. Prepare for scenario-based questions where you might need to outline how you would approach a specific credit risk challenge or project management situation.
✨Demonstrate Leadership and Teamwork
As a manager, your ability to lead and collaborate is crucial. Be ready to share examples of how you've successfully managed teams, engaged with clients, and contributed to projects. Highlight your experience in performance reviews and feedback processes.
