Real-Time Financial Crime Detection Engineers & Scientists

Alexander Barnes; England; On-site; GBP 70,000 - 120,000; Full time

Job summary

Alexander Barnes is partnering with a high-growth fintech to build out its financial crime product capability across fraud, transaction monitoring, and screening. Roles sit within product and engineering; you’ll define how detection works or build the systems it runs on.

You’ll work with data across transaction, authentication, behavior, and networks to identify patterns and signals and deploy scalable models in real-time.

Qualifications

• Hands-on experience in fraud, AML, or financial crime risk.
• Strong understanding of typologies and how they translate into detection logic.
• Python for analysis and modelling (pandas, numpy; ML exposure expected).
• Experience building, tuning, or deploying detection systems (rules and/or models).
• Ability to think about systems end-to-end. Not just models, but performance and outcomes.
• Comfortable working across product, engineering, and compliance.

Responsibilities

• Building and improving detection systems across fraud and AML.
• Working directly with transaction, auth, behavioural, and network data to identify patterns and signals.
• Developing detection logic across rules, models, and AI.
• Tuning systems continuously to reduce false positives and optimize coverage.

Skills

Fraud/AML experience

Python for analysis

Detection systems design

End-to-end systems thinking

Cross-functional collaboration

Tools

SQL

Job description

Alexander Barnes is partnering with a high-growth fintech to build out its financial crime product capability across fraud, transaction monitoring, and screening. Roles sit within product and engineering; you’ll define how detection works or build the systems it runs on.

You’ll work with data across transaction, authentication, behavior, and networks to identify patterns and signals and deploy scalable models in real-time.