Anti-Fraud Analyst

Обязанности

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 and identify where they need to be fixed or improved; Analyse client traffic and alert flows, measure false positives and missed fraud, and recommend concrete improvements; Build and optimise baseline rule sets and proactive alerts for common and emerging fraud scenarios; Turn analytical findings into clear product recommendations and support complex, data-intensive client cases when needed

Требования

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: you can identify data-quality issues, bias, leakage, overfitting, and misleading model results; 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, including the ability to validate their outputs; Fluency in English

Условия

Remote-first, trust-based culture; True flexibility; Extra time off; Work that matters; Compensation; Truly global; Growth built in; Celebrating your big moments; Team offsites

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