Job
Core
Improve fraud detection accuracy and signal quality across Sumsub products by investigating patterns, tuning detection logic, and optimizing rules/models.
Role type
Senior Anti-Fraud Analyst (Applied Data Science)
Builds
Fraud detection rule sets, proactive alerts, and detection logic for identity and business verification workflows.
Domain
Financial services, crypto, and compliance operations
Deliverable
production ML models
Required skills
Exploratory data analysis, supervised and unsupervised machine learning, anomaly detection, clustering, link-based/graph analysis, Python, SQL, ClickHouse, Trino, Superset, dbt, DataHub
Preferred skills
None stated
Technologies
ClickHouse, Trino, Superset, dbt, DataHub
Responsibilities
Explore live data to identify emerging fraud patterns and gaps in detection logic; Develop and tune fraud detection approaches using rules and models; Evaluate accuracy and predictive value of fraud signals; Analyse client traffic and alert flows to measure false positives/negatives; Build and optimize baseline rule sets and proactive alerts; Turn analytical findings into product recommendations.
Seniority
Senior, hands-on IC
