At a Glance
- Tasks: Build credit risk models and infrastructure from scratch in a dynamic fintech environment.
- Company: Join Lenkie, a mission-driven fintech empowering small businesses.
- Benefits: Enjoy competitive salary, equity, and a flexible hybrid working setup.
- Other info: Collaborate closely with leadership and engineering teams for career growth.
- Why this job: Make a real impact by shaping credit risk solutions for small businesses.
- Qualifications: 2-5 years of data science experience with Python and SQL skills.
The predicted salary is between 60000 - 80000 € per year.
Lenkie is on a mission to empower small businesses through faster access to financing. We're seeking a Senior Data Scientist with credit risk expertise to join our London team. This role offers the chance to build credit risk models and infrastructure from the ground up, working closely with leadership and engineering teams.
The ideal candidate will have 2–5 years of data science experience, proficiency in Python and SQL, and familiarity with credit risk in a fintech environment. Enjoy a competitive salary, equity, and a supportive hybrid working environment.
Founding Data Scientist, Credit Risk – Fintech, Hybrid London employer: Lenkie
Lenkie is an exceptional employer that champions innovation and collaboration in the fintech space. With a strong focus on employee growth, we offer competitive salaries, equity options, and a supportive hybrid work culture that fosters creativity and teamwork. Join us in London to make a meaningful impact on small businesses while advancing your career in a dynamic and empowering environment.
StudySmarter Expert Advice🤫
We think this is how you could land Founding Data Scientist, Credit Risk – Fintech, Hybrid London
✨Tip Number 1
Network like a pro! Reach out to people in the fintech space, especially those working in credit risk. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨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.
✨Tip Number 3
Prepare for interviews by brushing up on your Python and SQL skills. Be ready to discuss how you've used these tools in real-world scenarios, particularly in building models or analysing data.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Founding Data Scientist, Credit Risk – Fintech, Hybrid London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience in data science and credit risk. 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 your passion for fintech and how you can contribute to empowering small businesses with your expertise in credit risk.
Showcase Your Problem-Solving Skills:In your application, give examples of how you've tackled complex data challenges in the past. We love seeing candidates who can think critically and creatively about data science problems!
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 this exciting opportunity to join our London team!
How to prepare for a job interview at Lenkie
✨Know Your Data Science Stuff
Make sure you brush up on your data science fundamentals, especially around credit risk models. Be ready to discuss your previous projects and how you've used Python and SQL to solve real-world problems in a fintech context.
✨Understand Lenkie's Mission
Familiarise yourself with Lenkie's mission to empower small businesses. Think about how your skills can contribute to this goal and be prepared to share your thoughts on how data science can enhance access to financing.
✨Prepare for Technical Questions
Expect some technical questions during the interview. Practice explaining your thought process when building models and be ready to tackle hypothetical scenarios related to credit risk. This will show your problem-solving skills and expertise.
✨Show Your Team Spirit
Since you'll be working closely with leadership and engineering teams, highlight your collaborative experiences. Share examples of how you've successfully worked in cross-functional teams and how you can contribute to a supportive hybrid working environment.
