Senior Anti-Fraud Analyst

Responsibilities Explore live data to identify emerging fraud patterns, anomalous activity, and gaps in existing detection logic Develop and tune fraud detection approaches using rules, supervised and unsupervised models, anomaly detection, and link-based analysis Evaluate the accuracy, completeness, and predictive value of fraud signals Analyse client traffic and alert flows, measure false positives and missed fraud, and recommend improvements Build and optimise baseline rule sets and proactive alerts for common and emerging fraud scenarios Turn analytical findings into clear product recommendations Requirements 4+ years of experience in anti-fraud, risk analytics, applied data science, or another analytical role involving complex data and anomaly detection Strong knowledge of exploratory data analysis and classical machine learning, including supervised and unsupervised approaches Practical experience with anomaly detection, clustering, and link-based or graph analysis Hands-on experience in fraud prevention or fraud analytics Strong Python and SQL skills Hands-on experience with ClickHouse, Trino, Superset, dbt, DataHub, or comparable analytics tools Strong judgement when working with raw and imperfect data Ability to evaluate detection quality through false positives, false negatives, and other relevant metrics Ability to explain complex findings through clear logic, numbers, and concrete examples Confident but critical use of AI-assisted analytical tools Fluency in English About the Company Sumsub is the first AI-powered trust infrastructure for compliance operations at scale.

It connects identity and business verification, fraud prevention, transaction monitoring, and risk workflows, helping teams reduce manual work and enter new markets.