Senior Anti-Fraud Analyst

Sumsub

. Investigate live data to identify emerging fraud patterns, anomalous activity, and gaps in detection logic .

Posted 9/29/2026full-timeRemote • United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in fraud detection and risk analytics, utilizing advanced analytical techniques such as anomaly detection and machine learning. Proficient in Python and SQL, with hands-on experience in analytics tools to evaluate and improve fraud detection methodologies.

Highest-signal resume keywords

Fraud DetectionAnomaly DetectionMachine LearningPythonSQL

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Fraud AnalyticsExploratory Data AnalysisClusteringLink-Based AnalysisData Quality EvaluationFalse Positive MeasurementPredictive ModelingData Analysis

Soft Skills

Clear CommunicationCritical Thinking

Tools & Technologies

ClickHouseTrinoSupersetDbtDataHub

Industry Keywords

Risk AnalyticsData ScienceFraud Prevention

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

Investigate live data to identify emerging fraud patterns, anomalous activity, and gaps in 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
Analyze client traffic and alert flows
Measure false positives and missed fraud and recommend concrete improvements
Build and optimize baseline rule sets and proactive alerts for common and emerging fraud scenarios
Turn analytical findings into clear product recommendations
Support complex, data-intensive client cases when needed

Requirements

What you’ll need

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
Ability to 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

Benefits

Comp & perks

Remote-first, trust-based culture with no mandatory office days or attendance trackers
Choice of offices or coworking spaces in some locations
Flexible working hours without a fixed 9-to-5 schedule
Birthday holiday
10 personal days each year
Seven sick days without paperwork
Extra time off for Christmas and New Year
Role-specific learning opportunities and covered professional events
Financial bonuses for marriage and welcoming a new baby
Fully covered team offsite trips several times a year
Tools and hardware needed to perform the work