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- Tasks: Review and validate AI models while developing automated validation solutions.
- Company: Leading UK banking institution focused on innovation and risk management.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Why this job: Join a dynamic team and make a real impact in the world of AI and finance.
- Qualifications: Strong knowledge of machine learning, statistical modelling, and Python proficiency.
- Other info: Be part of a crucial risk function with excellent career advancement potential.
The predicted salary is between 36000 - 60000 £ per year.
A leading banking institution in the UK is seeking a Model Risk Data Scientist to review and independently validate AI models, develop automated validation solutions, and contribute to the analytics codebase. This role requires a strong grasp of machine learning and statistical modelling, alongside practical experience with Large Language Models and proficiency in Python. The successful candidate will be integral to the risk function, ensuring high standards of evaluation and model governance.
GenAI Validation Data Scientist – Model Risk employer: NatWest Group
Contact Detail:
NatWest Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land GenAI Validation Data Scientist – Model Risk
✨Tip Number 1
Network like a pro! Reach out to folks in the banking and AI sectors on LinkedIn. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your work with machine learning and Large Language Models. This is your chance to shine and demonstrate your expertise.
✨Tip Number 3
Prepare for interviews by brushing up on model validation techniques and Python coding challenges. We want you to feel confident and ready to tackle any question thrown your way!
✨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 take that extra step.
We think you need these skills to ace GenAI Validation Data Scientist – Model Risk
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with machine learning and statistical modelling. We want to see how your skills align with the role, so don’t be shy about showcasing your work with Large Language Models and Python.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about model risk and how you can contribute to our analytics codebase. Let us know what excites you about working in a leading banking institution.
Showcase Your Problem-Solving Skills: In your application, give examples of how you've tackled complex problems in the past. We love seeing candidates who can think critically and develop automated validation solutions, so share those experiences!
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 our team!
How to prepare for a job interview at NatWest Group
✨Know Your Models
Make sure you have a solid understanding of the AI models you'll be working with. Brush up on your knowledge of machine learning and statistical modelling, especially in relation to Large Language Models. Be ready to discuss specific examples of how you've validated models in the past.
✨Showcase Your Python Skills
Since proficiency in Python is key for this role, prepare to demonstrate your coding skills. You might be asked to solve a problem or explain your approach to developing automated validation solutions. Practise coding challenges that are relevant to model risk and data science.
✨Understand Model Governance
Familiarise yourself with the principles of model governance and evaluation standards. Be prepared to discuss how you would ensure high standards in your work and what processes you believe are essential for effective model risk management.
✨Ask Insightful Questions
Interviews are a two-way street! Prepare thoughtful questions about the company's approach to model risk and how they integrate AI into their operations. This shows your genuine interest in the role and helps you assess if it's the right fit for you.
