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- Tasks: Develop and validate statistical models for non-performing loan portfolios.
- Company: A growing fintech platform in Greater London with a dynamic environment.
- Benefits: Exciting opportunity to build analytics from scratch using cutting-edge technology.
- Why this job: Make a real impact in the fintech space with your data expertise.
- Qualifications: 5-8 years of experience in Data/Analytics, strong skills in Python and SQL.
- Other info: Join a team that values innovation and offers career growth.
The predicted salary is between 54000 - 84000 £ per year.
A growing fintech platform in Greater London is seeking a Data Analyst to develop and validate statistical models for analyzing non-performing loan portfolios. The ideal candidate will possess strong expertise in statistical modelling and machine learning, with experience in Python and SQL. This role offers an exciting opportunity to build an analytics function from the ground up using cutting-edge technology in a dynamic environment. Candidates should have 5-8 years of experience in Data/Analytics, ideally within a financial institution.
Senior Data Scientist: FinTech Investments & NPLs employer: Anonymous
Contact Detail:
Anonymous Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist: FinTech Investments & NPLs
✨Tip Number 1
Network like a pro! Reach out to folks in the fintech space, especially those working with data. A friendly chat can lead to insider info about job openings or even referrals.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your statistical models and machine learning projects. This is your chance to shine and demonstrate what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your Python and SQL skills. Be ready to discuss your past experiences with non-performing loans and how you've tackled similar challenges.
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team. Plus, it makes the process smoother for everyone involved.
We think you need these skills to ace Senior Data Scientist: FinTech Investments & NPLs
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in statistical modelling and machine learning. We want to see how your skills in Python and SQL can shine through, so don’t hold back on showcasing relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to tell us why you’re the perfect fit for this role. Share specific examples of your work with non-performing loan portfolios and how you've used analytics to drive results in previous positions.
Showcase Your Passion for FinTech: We love candidates who are genuinely excited about the fintech space! In your application, let us know what draws you to this industry and how you envision contributing to our growing platform.
Apply Through Our Website: To make sure your application gets the attention it deserves, apply directly through our website. It’s the best way for us to keep track of your application and ensure it reaches the right people!
How to prepare for a job interview at Anonymous
✨Know Your Stats
Brush up on your statistical modelling and machine learning concepts. Be ready to discuss specific models you've developed or validated in the past, especially those related to non-performing loans. This will show your expertise and how you can contribute to building the analytics function.
✨Showcase Your Tech Skills
Make sure you’re comfortable discussing your experience with Python and SQL. Prepare examples of projects where you used these tools to solve real-world problems. This will demonstrate your technical proficiency and ability to work with cutting-edge technology.
✨Understand the FinTech Landscape
Familiarise yourself with the current trends in the fintech industry, particularly around investments and non-performing loans. Being able to speak knowledgeably about the market will impress interviewers and show that you're genuinely interested in the role.
✨Prepare Questions
Have a few insightful questions ready to ask at the end of the interview. This could be about the company's future plans for their analytics function or how they measure success in this role. It shows that you’re engaged and thinking critically about how you can fit into their team.
