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- Tasks: Lead client projects and engage in quantitative risk analysis within the credit life cycle.
- Company: Join a leading financial services firm in London with a focus on innovation.
- Benefits: Competitive salary, professional development, and opportunities for career advancement.
- Other info: Collaborative team environment with strong emphasis on personal growth and client relationships.
- Why this job: Make an impact in credit risk management while working with cutting-edge AI solutions.
- Qualifications: Bachelor's degree in relevant fields and experience in financial services required.
The predicted salary is between 60000 - 80000 £ 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 in London employer: Campion Pickworth
Contact Detail:
Campion Pickworth Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Credit Data Scientist in London
✨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 a Credit Data Scientist role. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects related to credit risk, machine learning, or any relevant software development. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your knowledge of Probability of Default and Loss Given Default. Be ready to discuss how you've applied these concepts in past roles or projects, as this will demonstrate your expertise in the field.
✨Tip Number 4
Don't forget to apply through our website! We have some fantastic opportunities waiting for you, and applying directly can sometimes give you an edge over other candidates. Plus, it shows you're genuinely interested in joining our team!
We think you need these skills to ace Credit Data Scientist in London
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 what we're looking for!
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 your experience with software like Python or R. This helps us see you in action.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Explain why you're passionate about credit risk and how you can contribute to our team. Keep it engaging and make sure to connect your experiences to the job description.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It’s the best way for us to receive 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 real-world problems. This will demonstrate your technical prowess and relevance to the role.
✨Team Player Vibes
Since the role involves working closely with teams, be prepared to share experiences where you collaborated effectively. Talk about how you maintained communication and supported your colleagues, as this will show you're a great fit for their team-oriented culture.
✨Client Engagement Experience
The job requires developing productive relationships with clients. Think of specific instances where you successfully managed client expectations or contributed to business opportunities. This will illustrate your ability to drive engagement and add value to their client interactions.