We are looking for a Fraud Data Integration Analyst to join our Financial Operations & Risk team.
This role bridges data analytics, fraud prevention, and financial governance, ensuring unified, accurate, and timely data to support fraud detection, chargeback monitoring, and network compliance.
The ideal candidate combines strong SQL and data management skills with an understanding of fraud systems, financial flows, and operational processes.
Key Responsibilities
- Develop and maintain dashboards that track fraud rates, false positives, decision accuracy, chargeback ratios, and financial exposure.
- Conduct statistical analysis to support fraud model calibration and business impact measurement.
- Evaluate fraud detection performance and document improvements and measurable outcomes .
Data Integration & System Maintenance
Build automated and semi-automated workflows to ingest, clean, and load data from :
Fraud detection and risk scoring platforms.Transactional databases.Internal KYC or onboarding systems.External acquirer, chargeback, and operational reports (often in CSV or Excel format).Ensure data integrity, reconciliation, and standardization across sources.Maintain a centralized chargeback registry with full traceability to transactions.Reconcile chargeback data from acquirer reports and internal systems.Track performance against Visa and Mastercard program thresholds.Cross-Functional Collaboration
Contribute to initiatives that strengthen financial control, settlement, and operational efficiency.Partner with IT and data engineering to enhance automation and data governance.Support Finance Ops and Compliance team 's with validated fraud and chargeback reports.Qualifications
Education
Bachelor’s degree in Economics, Statistics, Accounting, Finance, or related field.Experience
3+ years of experience in data analytics, financial risk, or fraud prevention (ideally in fintech, payments, or e-commerce).Proficiency in SQL, Excel, and database management.Experience with data automation or scripting (Python, R, or similar).Experience with data visualization tools (e.g., Looker, Power BI, or similar) is a plus.Skills
High attention to detail and process discipline.Strong analytical mindset, and able to operate cross-functionally in a fast-paced environment.Seniority Level
Mid-Senior levelEmployment Type
Full-timeJob Function
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