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- Tasks: Lead credit risk projects and engage with clients to drive business opportunities.
- Company: Dynamic financial services firm based in London, focused on innovation.
- Benefits: Competitive salary, career development, and a collaborative team environment.
- Why this job: Make an impact in the financial sector using your data science skills.
- Qualifications: Experience in financial services and strong analytical skills required.
- Other info: Opportunity for growth in a fast-paced, supportive workplace.
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 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 - Manager 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 opportunities. A friendly chat can lead to referrals that might just land you that Credit Data Scientist role.
✨Tip Number 2
Prepare for interviews by brushing up on your knowledge of Probability of Default and Loss Given Default. We recommend creating a cheat sheet with key concepts and examples to help you articulate your expertise during those tricky questions.
✨Tip Number 3
Showcase your technical skills! If you've got experience with Python, R, or SQL, make sure to highlight specific projects where you applied these tools. We love seeing real-world applications of your skills in action!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we’re always looking for talented individuals like you to join our team and drive innovation in credit risk management.
We think you need these skills to ace Credit Data Scientist - Manager 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 other key areas mentioned in the job description. This helps us see your practical experience.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Explain why you're passionate about the role and how you can contribute to our team. We love seeing enthusiasm and a clear understanding of the position, so make it personal and engaging.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you get all the updates directly. Plus, it shows you're keen on joining our team at StudySmarter!
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’re not just familiar with the theory but can also translate it into practice.
✨Showcase Your Technical Skills
Make sure you 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 how you can contribute to the team’s success.
✨Engage with Real-World Scenarios
Be prepared to discuss real-world applications of machine learning techniques in credit risk management. Think of specific instances where you’ve implemented these strategies and the outcomes. This will help the interviewers see your practical understanding of the role.
✨Build Rapport with Stakeholders
Since client management is key for this role, think about how you’ve successfully built relationships in previous positions. Share anecdotes that illustrate your communication skills and ability to manage expectations. This will show that you can effectively lead client engagements.
