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- Tasks: Lead data science projects and analyse consumer risk trends for BNPL products.
- Company: Global financial services company based in London with a focus on innovation.
- Benefits: Hybrid work options, competitive salary, and opportunities for professional growth.
- Why this job: Make a real impact on credit decision-making in a fast-paced environment.
- Qualifications: Experience in credit risk management and strong analytical skills required.
- Other info: Join a dynamic team and shape the future of financial services.
The predicted salary is between 48000 - 72000 £ per year.
A global financial services company in London is seeking a Data Science Manager to oversee credit risk strategies for Buy Now Pay Later products. The successful candidate will lead data science projects, analyze consumer risk trends, and collaborate with cross-functional teams to enhance credit decision-making.
Experience in credit risk management and strong analytical skills, alongside a Bachelor's degree, are essential. This role supports hybrid work arrangements, providing the flexibility to work both in the office and remotely.
Lead BNPL Credit Risk & Data Science Manager employer: PayPal, Inc.
Contact Detail:
PayPal, Inc. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead BNPL Credit Risk & Data Science Manager
✨Tip Number 1
Network like a pro! Reach out to folks in the financial services and data science sectors. LinkedIn is your best mate here—connect with people who work at companies you're interested in, and don't be shy about asking for informational chats.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data science projects, especially those related to credit risk. This will give potential employers a taste of what you can bring to the table and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your knowledge of BNPL products and credit risk strategies. Be ready to discuss how you've tackled similar challenges in the past and how you can contribute to enhancing credit decision-making.
✨Tip Number 4
Don't forget to apply through our website! We love seeing applications directly from candidates who are genuinely interested in joining our team. Plus, it gives us a chance to see your enthusiasm right from the start!
We think you need these skills to ace Lead BNPL Credit Risk & Data Science Manager
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in credit risk management and data science. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about BNPL products and how your analytical skills can enhance our credit decision-making processes. Keep it engaging and personal!
Showcase Your Analytical Skills: In your application, give examples of how you've used data to drive decisions in previous roles. We love seeing concrete results, so if you’ve improved credit strategies or analysed consumer trends, let us know!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy to do!
How to prepare for a job interview at PayPal, Inc.
✨Know Your Credit Risk Fundamentals
Make sure you brush up on the key concepts of credit risk management, especially as they relate to Buy Now Pay Later products. Be ready to discuss how you would approach analysing consumer risk trends and what strategies you would implement.
✨Showcase Your Data Science Skills
Prepare to talk about your previous data science projects, particularly those that involved credit risk. Highlight specific tools and methodologies you've used, and be ready to explain how your analytical skills can enhance credit decision-making.
✨Collaboration is Key
Since this role involves working with cross-functional teams, think of examples where you've successfully collaborated with others. Be prepared to discuss how you communicate complex data insights to non-technical stakeholders.
✨Embrace the Hybrid Work Model
With the flexibility of hybrid work arrangements, consider how you manage your time and productivity in both office and remote settings. Share your strategies for staying connected with your team and ensuring effective collaboration, regardless of where you're working from.
