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For Companies At a Glance
- Tasks: Lead lending strategies and collaborate with data scientists to boost profitability.
- Company: Join a top UK FinTech revolutionising lending through data-driven decisions.
- Benefits: Enjoy a £100,000 salary, hybrid work, company equity, and exciting international trips.
- Why this job: Make a real impact in a growing company while working with innovative tech and talented teams.
- Qualifications: Must have SQL and Python skills, experience in consumer lending, and a STEM degree from a Russell Group University.
- Other info: This role offers a unique chance to shape the future of lending.
The predicted salary is between 60000 - 84000 £ per year.
This is an exciting opportunity with a leading UK FinTech that focuses on harnessing data to enhance their lending decisions. This business has been growing in recent years and is now in an excellent position. This role offers the chance to work closely with the data science team to drive impact across their lending strategies and broader business profitability.
THE ROLE
- Monitor and adjust lending strategies across the customer lifecycle to enhance profitability and decisioning.
- Collaborate with the data science team to drive model performance and implementation of innovative machine learning models.
- Analyse trends in lending portfolios to drive insight and enhance business performance.
- Lead the incorporation of new data sources to enhance and improve decisioning.
YOUR SKILLS AND EXPERIENCE
- Previous experience in and knowledge of SQL and Python is essential.
- Experience in developing lending strategies in a consumer lending environment.
- Experience monitoring a lending portfolio and customer trends.
- STEM degree from a Russell Group University.
SALARY AND BENEFITS
- Base salary of up to £100,000.
- Hybrid work model.
- Company equity.
- Broader company benefits including international trips.
HOW TO APPLY
Please register your interest by sending your CV to Rosie Walsh through the ‘Apply’ link.
Contact Detail:
LinkedIn Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Credit Risk Manager
✨Tip Number 1
Network with professionals in the FinTech industry, especially those who work in credit risk management. Attend relevant meetups or webinars to connect with potential colleagues and learn more about the company culture at StudySmarter.
✨Tip Number 2
Familiarise yourself with the latest trends in machine learning and data analytics as they relate to lending strategies. Being able to discuss recent advancements can set you apart during informal conversations or interviews.
✨Tip Number 3
Prepare to showcase your experience with SQL and Python by thinking of specific projects or challenges you've tackled using these skills. Be ready to discuss how you applied them to improve lending strategies or portfolio performance.
✨Tip Number 4
Research StudySmarter's current lending strategies and any recent changes in their approach. This knowledge will help you engage in meaningful discussions during interviews and demonstrate your genuine interest in the role.
We think you need these skills to ace Senior Credit Risk Manager
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with SQL and Python, as well as your background in developing lending strategies. Use specific examples that demonstrate your skills in monitoring lending portfolios and analysing customer trends.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for the FinTech industry and your understanding of how data can enhance lending decisions. Mention your collaboration with data science teams and any innovative projects you've been involved in.
Highlight Relevant Experience: In your application, emphasise your previous roles related to credit risk management and consumer lending. Discuss any successful strategies you implemented and the impact they had on profitability.
Proofread Your Application: Before submitting, carefully proofread your CV and cover letter for any errors or typos. A polished application reflects your attention to detail, which is crucial for a Senior Credit Risk Manager role.
How to prepare for a job interview at LinkedIn
✨Showcase Your Technical Skills
Make sure to highlight your experience with SQL and Python during the interview. Be prepared to discuss specific projects where you used these skills to develop lending strategies or analyse data.
✨Demonstrate Your Understanding of Lending Strategies
Be ready to talk about your previous experience in developing lending strategies. Discuss how you've monitored portfolios and adapted strategies based on customer trends, as this will show your ability to drive profitability.
✨Collaborate Effectively
Since this role involves working closely with the data science team, emphasise your collaborative skills. Share examples of how you've successfully worked with cross-functional teams to implement innovative solutions.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving abilities. Prepare for scenario-based questions where you might need to analyse a lending portfolio or suggest improvements based on hypothetical data trends.
