At a Glance
- Tasks: Lead credit risk projects and engage with clients to drive business opportunities.
- Company: Join a leading financial services firm in the heart of London.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Other info: Dynamic team environment with a focus on collaboration and development.
- Why this job: Make an impact in the financial sector using your analytical skills and innovative solutions.
- Qualifications: Bachelor's degree in a relevant field and experience in financial services required.
The predicted salary is between 43200 - 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
Our client offers an exceptional work environment in the heart of London, where innovation meets collaboration. As a Credit Data Scientist - Manager, you will benefit from a culture that prioritises professional growth, with ample opportunities for career advancement and skill development. The company fosters a supportive atmosphere, encouraging teamwork and open communication, making it an ideal place for those seeking meaningful and rewarding employment in the financial services sector.
StudySmarter Expert Advice🤫
We think this is how you could land Credit Data Scientist - Manager
✨Tip Number 1
Network like a pro! Reach out to your connections in the financial services sector and let them know you're on the lookout for opportunities. You never know who might have a lead or can put in a good word for you.
✨Tip Number 2
Prepare for those interviews by brushing up on your knowledge of credit risk and machine learning techniques. We recommend practising common interview questions and even doing mock interviews with friends to build your confidence.
✨Tip Number 3
Showcase your skills! Create a portfolio that highlights your projects, especially those involving Python, R, or SQL. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 4
Don't forget to apply through our website! We’ve got loads of opportunities waiting for talented individuals like you. Plus, it’s a great way to ensure your application gets seen by the right people.
We think you need these skills to ace Credit Data Scientist - Manager
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Credit Data Scientist role. Highlight your experience in Financial Services and any relevant projects you've worked on. We want to see how your skills align with the job description!
Showcase Your Skills:Don’t just list your skills; demonstrate them! Use specific examples from your past work that showcase your knowledge of Probability of Default, Loss Given Default, and other key areas mentioned in the job description. This will help us see your expertise in action.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Explain why you’re passionate about the role and how your background makes you a perfect fit. We love seeing enthusiasm and a clear understanding of the position.
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Campion Pickworth
✨Know Your Numbers
As a Credit Data Scientist, you'll need to be comfortable with key metrics like Probability of Default (PD) and Loss Given Default (LGD). Brush up on these concepts and be ready to discuss how you've applied them in past roles. This shows you understand the core of credit risk.
✨Showcase Your Technical Skills
Make sure to highlight your experience with software like Python, R, or SQL during the interview. Prepare examples of projects where you used these tools to solve complex problems. This will demonstrate your technical prowess and ability to contribute to the team.
✨Engage with Real-World Scenarios
Be prepared to discuss real-world applications of machine learning techniques in credit risk. Think of specific instances where you've implemented these strategies and the outcomes. This will show your practical understanding and innovative thinking.
✨Build Rapport with Stakeholders
Since client management is key for this role, practice how you would communicate complex data insights to non-technical stakeholders. Share examples of how you've successfully built relationships in previous roles, as this will highlight your interpersonal skills.
