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- Tasks: Lead a team to develop machine learning models for credit scoring and fraud detection.
- Company: A leading financial technology company in the UK with a focus on innovation.
- Benefits: Competitive salary, hybrid work model, and excellent career development opportunities.
- Why this job: Make a real impact in the financial sector while leading a talented team.
- Qualifications: Over 6 years of data science experience and strong leadership skills.
- Other info: Collaborative environment with a focus on delivering high-quality solutions.
The predicted salary is between 48000 - 72000 £ per year.
A leading financial technology company in the UK is seeking a Data Science Manager to lead a team of data scientists in developing machine learning models for credit scoring, fraud detection, and collections. The ideal candidate will have over 6 years of experience in data science, with a strong emphasis on leadership roles. This position involves collaboration with various teams to deliver innovative data-driven solutions, ensuring high-quality machine learning outputs for customers across Nigeria and beyond. Competitive benefits and a hybrid work model are offered.
Data Science Manager - Credit Risk & Fraud Analytics in London employer: Kuda
Contact Detail:
Kuda Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Science Manager - Credit Risk & Fraud Analytics in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the fintech space, especially those who work in data science. A friendly chat can lead to insider info about job openings or even a referral.
✨Tip Number 2
Show off your skills! Prepare a portfolio showcasing your best machine learning projects, especially those related to credit scoring and fraud detection. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Ace the interview! Research common questions for data science managers and practice your responses. Be ready to discuss your leadership style and how you've successfully led teams in the past.
✨Tip Number 4
Apply through our website! We’ve got loads of opportunities waiting for you. Plus, applying directly shows your enthusiasm and commitment to joining our team.
We think you need these skills to ace Data Science Manager - Credit Risk & Fraud Analytics in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in data science, especially in leadership roles. We want to see how you've led teams and developed machine learning models, so don’t hold back on those details!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're the perfect fit for the Data Science Manager role. Share specific examples of your work in credit scoring and fraud detection to grab our attention.
Showcase Your Collaboration Skills: Since this role involves working with various teams, make sure to highlight any collaborative projects you've been part of. We love seeing how you’ve worked with others to deliver innovative solutions!
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 in our team!
How to prepare for a job interview at Kuda
✨Know Your Data Science Stuff
Make sure you brush up on your data science fundamentals, especially around machine learning models relevant to credit scoring and fraud detection. Be ready to discuss your past projects and how they relate to the role, showcasing your technical expertise and leadership experience.
✨Showcase Your Leadership Skills
As a Data Science Manager, you'll need to demonstrate your ability to lead a team effectively. Prepare examples of how you've successfully managed teams in the past, resolved conflicts, and fostered collaboration. Highlight your approach to mentoring junior data scientists and driving innovation.
✨Understand the Business Context
Familiarise yourself with the financial technology landscape, particularly in credit risk and fraud analytics. Research the company’s products and services, and think about how your work can contribute to their goals. This will show that you're not just a techie but also understand the business side of things.
✨Prepare for Collaborative Questions
Since this role involves working with various teams, be ready to answer questions about collaboration and communication. Think of specific instances where you’ve worked cross-functionally to deliver data-driven solutions. This will highlight your ability to work well with others and drive results.
