Meghana K

Fraud & Risk Data Analyst | SQL, Python, R, Power BI, BigQuery | Transaction Monitoring, KYC/AML, Anomaly Detection | MS in Business Analytics

Role
Risk & Fraud Data Analyst at Barclays
Location
San Jose, CA, US
LinkedIn followers
500 followers

About Meghana K

A data driven problem solver and has an experience in solving evidence based Quality…

Experience

  1. Risk & Fraud Data Analyst

    Barclays

    Aug 2024 — Present

    Developed fraud scoring models using dbt and BigQuery for SaaS onboarding journeys, improving detection of synthetic identities by 92%.• Engineered multi-touch funnel metrics in SQL to identify synthetic identity fraud and account takeover patterns in KYC onboarding flows.• Created Hex dashboards with dynamic filters to visualize fraud trends across geos and channels, reducing investigative cycle time by 40%.• Implemented anomaly detection on transactional behavior using unsupervised learning in Python (Isolation Forest, DBSCAN) to flag potential fraud cases.• Built A/B test frameworks using statsmodels and SciPy to assess risk-friction tradeoffs of new fraud controls; supported policy optimizations.• Automated ingestion of internal/third-party fraud signals (e.g, 3p device fingerprinting, Velocity checks) with event-based triggers and Python ETL pipelines.

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Meghana K — Risk & Fraud Data Analyst at Barclays in San Jose, CA, US | Unifers