RBS
Data Scientist, Economic Crime Hub
Get notified of more jobs like this · No spam, ever
How your CV stacks up
Upload your CV to see how well it fits this job role
?%
Join us as a Data Scientist, Economic Crime Hub
You’ll design and implement data science tools and methods which harness our data that use our data to prevent fraud and scams, reduce customer harm and financial losses, and improve the accuracy and efficiency of fraud decisioning. We’ll look to you to actively participate in the Fraud, Engineering and Data community to identify and deliver opportunities to support the bank’s strategic direction through better use of data. This is an opportunity to promote data literacy education with business stakeholders supporting them to foster a data driven culture and to make a real impact with your work.
What you'll do
As a Data Scientist, you’ll combine statistical analysis, machine learning, generative AI and software engineering to develop practical, responsible solutions to fraud and scam challenges. You’ll work with fraud stakeholders and customer teams to understand their needs, form clear hypotheses and identify data-led solutions that improve fraud detection, reduce false positives, support timely intervention and deliver measurable fraud prevention and operational.
Reasons to use Rodeo
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
It searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
You’ll also be:
- Working with fraud stakeholders to translate fraud and scam challenges into clear analytical questions and measurable outcomes
- Applying a software engineering and product development practices to build reusable pipelines, test changes, and deploy scalable solutions in an Agile environment
- Selecting, building, training and testing machine learning models, fraud strategies and AI applications, balancing fraud detection and business value with customer impact, operational capacity, model risk and ethical considerations
- Monitoring internal and third-party fraud models for performance, data quality, drift and business effectiveness, recommending corrective action where needed
- Investigating emerging fraud patterns, unusual alerts and missed fraud events, turning findings into practical improvements and maintaining clear evidence for governance, audit and regulatory review
The skills you'll need
Get help with your application
Your very own career expert that helps elevate your application to the next level.
You’ll need a strong academic background in a STEM discipline such as Mathematics, Physics, Engineering or Computer Science. You’ll have experience with statistical modelling and machine learning techniques applied to fraud or other complex risk problems involving rare events.
You’ll also demonstrate:
- The ability to use data to solve business problems from hypotheses through to resolution
- Experience using programming language and software engineering fundamentals
- Experience of Cloud applications and options
- Experience in synthesising, translating and visualising data and insights for key stakeholders
- Experience in model monitoring, model-risk governance and documenting analytical decisions for review and challenge is desirable.
- Knowledge of how Large Language Models and agentic AI can support fraud and scam analysis, and the controls required to manage the risks of using those applications, is also desirable.
Hours
35
Job Posting Closing Date
12/10/2026
Ways of Working
Remote First
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
Location