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 supportive hybrid work culture.
- 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 expertise.
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 open doors and give you insights that might just land you that interview.
✨Tip Number 2
Show off your skills! Prepare a portfolio showcasing your data science projects, especially those related to credit risk. This will not only demonstrate your expertise but also make you stand out during interviews.
✨Tip Number 3
Practice makes perfect! Get ready for technical interviews by brushing up on Python and SQL. We recommend doing mock interviews with friends or using online platforms to simulate the real deal.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. 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 🫡
Show Your Passion for Fintech:When writing your application, let us see your enthusiasm for the fintech industry. Share any relevant experiences or projects that highlight your interest in empowering small businesses through data science.
Highlight Your Technical Skills:Make sure to showcase your proficiency in Python and SQL clearly. We want to see how you've used these skills in previous roles, especially in relation to credit risk models or similar projects.
Tailor Your Application:Don’t just send a generic application! Tailor your CV and cover letter to reflect the specific requirements of the Founding Data Scientist role. Mention how your experience aligns with building credit risk models and working in a hybrid environment.
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
Dive into Lenkie's mission of empowering small businesses. Show that you’re not just interested in the role but also passionate about how data science can drive better financing solutions for these businesses.
✨Prepare for Technical Questions
Expect some technical questions during the interview. Practice explaining your thought process when building models and be prepared to tackle case studies or hypothetical scenarios related to credit risk.
✨Show Your Team Spirit
Since this role involves working closely with leadership and engineering teams, highlight your collaboration skills. Share examples of how you've successfully worked in cross-functional teams to achieve common goals.
