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- Tasks: Analyse user behaviour and innovate risk strategies using SQL and Python.
- Company: Leading fintech company in the UK with a focus on credit products.
- Benefits: Competitive salary, equity options, and flexible remote or hybrid work.
- Why this job: Join a collaborative team and make a real impact in credit risk management.
- Qualifications: Over 4 years of data science experience, especially in risk-focused roles.
- Other info: Exciting opportunity for career growth in a dynamic fintech environment.
The predicted salary is between 48000 - 84000 £ per year.
A leading fintech company in the UK is looking for a Lead/Senior Data Scientist to enhance the performance of credit products. The role involves analyzing user behavior using SQL and Python, conducting root-cause analyses, and working within a collaborative team to innovate risk strategies.
Candidates must have over 4 years of data science experience, particularly in risk-focused roles. This position offers a competitive compensation package, including equity and benefits, and the opportunity to work remotely or in a hybrid model.
Lead Data Scientist, Credit Risk — Remote & Equity in London employer: Wayfindi
Contact Detail:
Wayfindi Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data Scientist, Credit Risk — Remote & Equity in 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 insider info about job openings and even referrals.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your SQL and Python projects, especially those related to user behaviour analysis. This will give you an edge when discussing your experience during interviews.
✨Tip Number 3
Prepare for those tricky questions! Brush up on root-cause analysis techniques and be ready to discuss how you've tackled similar challenges in past roles. We want to see your problem-solving skills in action!
✨Tip Number 4
Don’t forget to 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 Lead Data Scientist, Credit Risk — Remote & Equity in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in data science, especially in risk-focused roles. We want to see how your skills in SQL and Python can enhance our credit products!
Showcase Your Projects: Include specific examples of projects where you've analysed user behaviour or conducted root-cause analyses. This helps us understand your hands-on experience and innovative thinking.
Be Clear and Concise: When writing your cover letter, keep it straightforward. We appreciate clarity, so make sure you communicate your passion for data science and how you can contribute to our team.
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 don’t miss out on any important updates!
How to prepare for a job interview at Wayfindi
✨Know Your Data Science Stuff
Make sure you brush up on your SQL and Python skills before the interview. Be ready to discuss specific projects where you've used these tools, especially in risk-focused roles. This will show that you not only have the technical know-how but also practical experience.
✨Understand Credit Risk
Familiarise yourself with credit risk concepts and strategies. Be prepared to discuss how you've approached root-cause analyses in past roles. Showing a solid understanding of the fintech landscape and how data science can enhance credit products will set you apart.
✨Collaborative Mindset
Since this role involves working within a team, be ready to share examples of how you've successfully collaborated with others. Highlight any experiences where you’ve innovated risk strategies as part of a group, as this will demonstrate your ability to work well in a collaborative environment.
✨Ask Insightful Questions
Prepare some thoughtful questions about the company's approach to credit risk and their data science team dynamics. This shows your genuine interest in the role and helps you gauge if the company culture aligns with your values.
