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AML Risk and Controls Officer
OtherWorkplace — Europe
Published on 2026-11-11
These details were extracted automatically from the original listing. They may not be complete or fully up to date — it's worth checking the original job post.
About this role
Investigate financial crime patterns that are not detected by existing transaction monitoring controls, and translate confirmed findings into tested detection rules. Partner with the AML Risk Manager to assess control effectiveness, reduce false negatives, and maintain coverage of the FinCrime Scenarios Library.
About the company
Finom is a European business banking and finance platform that combines accounts, cards, invoicing, and accounting tools for SMEs and entrepreneurs.
Stack
SQLDatabricksMetabasePower BIPython
What you'll do
- Investigate transactional anomalies using internal and external sources and document confirmed typologies.
- Design, back-test, release, and monitor transaction monitoring rules and model features.
- Track control coverage, false negatives, alert volumes, hit rates, false positives, and rule performance.
- Validate internally developed machine learning models and monitor their performance in production.
- Create training materials for Transaction Monitoring and Quality Assurance teams.
- Improve financial crime processes and draft or review requirements for relevant system features.
What we're looking for
- At least 2 years in Second Line of Defence at a regulated financial institution, or 3 years in senior Transaction Monitoring or Process Owner roles.
- Strong knowledge of AML regulation and transaction-based money laundering typologies.
- Hands-on SQL skills, including queries across large transaction tables.
- Experience with analytics and visualisation tools such as Databricks, Metabase, or Power BI.
- Understanding of rule testing, back-testing, false positives and negatives, hit rate, precision, and recall.
- Structured, evidence-based approach and ability to work independently in a fast-moving startup.
Nice to have
- Practical use of AI tools for investigation or analysis, with careful validation of outputs.
- Python or similar scripting experience.
- Experience validating or monitoring machine learning models used in AML detection.
- Experience in a fintech, neobank, or SME-focused payment institution.