Senior Data Scientist (FinCrime / Fraud) in City of London
New Yesterday
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Job Description
Job Title: Senior Data Scientist ( AI / ML Engineer)
Salary: up to £135k (+ very generous early-stage equity, £100k+)
Location: Central London, EC1 (3 office day/week)
Company: B2B FinTech / Fraud Prevention
Employees : ~25
Funding : $15m+ (Series A)
This London startup is building a new intelligence layer designed to bring more context and security to digital payments. Their technology analyses transactions in real time, gathering signals from multiple sources to determine whether a payment is legitimate or potentially fraudulent.
The platform combines distributed data systems, real-time investigations and AI-driven decisioning to help financial institutions detect scams while allowing legitimate payments to flow without unnecessary friction. Within 2 years of being founded, they're working with most Tier 1 banks and payment providers in the UK - and are just getting started!
They are now looking for an experienced Data Scientist ( AI/ML Engineer) with deep fraud or financial crime experience (ideally APP fraud exposure) to join at an early stage and help shape the core intelligence powering the platform.
Key responsibilities:
Designing and deploying machine learning models used to detect fraud and financial crime in payment flows
Building features from heterogeneous data sources, including transaction data, contextual signals and unstructured information
Improving systems that extract useful signals from fragmented or unstructured data sources
Building reliable ML infrastructure to train, deploy and monitor models in production environments
Working closely with product and engineering teams to ensure models improve real-world fraud outcomes
Identifying the fraud signals, typologies and data sources that meaningfully improve detection capability
Experimenting with both classical ML techniques and newer AI approaches where appropriate
Helping shape data strategy, including how feedback loops and labelling pipelines are built to improve models over time
This role is focused on shipping production systems rather than academic research .
✅ Must have requirements:
Strong practical experience building fraud detection systems or financial crime models in production
Deep FinCrime / FinTech / Payments domain expertise
Product mindset - focus on improving real-world outcomes, not just model metrics.
Experience working in fast-moving environments where systems are built from scratch and priorities evolve quickly.
Experience working with heterogeneous datasets (transaction data, enrichment signals, text, network signals etc.)
Familiarity with model monitoring, drift detection and retraining pipelines
Strong SQL and data engineering capability
Strong programming skills in Python
Bonus points for:
Exposure to / understanding of APP Fraud, payment fraud or transaction monitoring
Previous experience working in an early stage start-up and/or high growth scale up
Exposure to newer approaches such as LLM-powered systems
Cloud infrastructure / data platforms experience, ideally GCP
VISA sponsorship is available if needed.
If you are interested in applying for this job please press the Apply Button and follow the application process. Energy Jobline wishes you the very best of luck in your next career move.
- Location:
- City Of London
- Job Type:
- FullTime
