At a Glance
- Tasks: Build advanced credit risk models using cutting-edge ML techniques.
- Company: Join Harnham's specialist AI & Machine Learning team in a dynamic environment.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Other info: Work 3 days in the office in Leeds or Nottingham.
- Why this job: Make a real impact in the fintech space with innovative data solutions.
- Qualifications: Experience in banking or fintech with strong Python and SQL skills.
The predicted salary is between 60000 - 80000 € per year.
Harnham is seeking a professional to join their specialist AI & Machine Learning team in Leeds. The role focuses on building modern credit risk and decisioning models, moving beyond traditional scorecards to advanced ML techniques.
Responsibilities include:
- Enhancing lending models
- Applying predictive modelling
- Collaborating with engineering teams
Ideal candidates have a background in banking or fintech with strong skills in Python and SQL. The position requires 3 days in the office (Leeds or Nottingham).
Lead Data Scientist - Credit Risk ML (Leeds/Nottingham) employer: Harnham
Harnham is an exceptional employer that fosters a dynamic and innovative work culture, particularly within its AI & Machine Learning team. Employees benefit from a collaborative environment that encourages professional growth through hands-on experience with cutting-edge technologies in credit risk modelling. With a strong focus on employee development and a flexible working arrangement in vibrant locations like Leeds and Nottingham, Harnham offers a rewarding career path for those passionate about advancing their skills in the fintech sector.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Data Scientist - Credit Risk ML (Leeds/Nottingham)
✨Tip Number 1
Network like a pro! Reach out to folks in the banking or fintech space, especially those who work with AI and Machine Learning. A friendly chat can open doors and give you insights that might just land you that Lead Data Scientist role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects in Python and SQL, especially those related to credit risk and predictive modelling. This will not only impress potential employers but also give you confidence during interviews.
✨Tip Number 3
Prepare for technical interviews by brushing up on your ML techniques and decisioning models. Practice explaining your thought process clearly, as collaboration with engineering teams is key in this role.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that match your skills, and applying directly can sometimes give you an edge over other candidates. Let’s get you that dream job!
We think you need these skills to ace Lead Data Scientist - Credit Risk ML (Leeds/Nottingham)
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience in banking or fintech, especially any work with credit risk models. We want to see how your skills in Python and SQL shine through!
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 ML techniques and how you've enhanced lending models in the past.
Showcase Your Technical Skills:Don’t forget to mention your proficiency in Python and SQL! We’re looking for candidates who can demonstrate their technical prowess, so include relevant projects or achievements.
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 from us!
How to prepare for a job interview at Harnham
✨Know Your Models
Make sure you can discuss the credit risk and decisioning models you've worked on in detail. Be ready to explain how you've applied advanced ML techniques and what impact they had on lending outcomes.
✨Brush Up on Python and SQL
Since strong skills in Python and SQL are crucial for this role, review your past projects and be prepared to demonstrate your coding abilities. You might even be asked to solve a problem on the spot, so practice coding challenges beforehand.
✨Collaborate Like a Pro
This role involves working closely with engineering teams, so be ready to share examples of how you've successfully collaborated in the past. Highlight your communication skills and how you’ve navigated cross-functional projects.
✨Understand the Fintech Landscape
Having a background in banking or fintech is key. Stay updated on industry trends and be prepared to discuss how they influence credit risk modelling. This shows your passion for the field and your commitment to staying informed.
