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.