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shivapriya pillalamarri
Mid-level AI/ML Engineer specializing in financial analytics and production ML systems
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About
Analytics candidate with experience in financial transaction and fraud detection projects, combining SQL data preparation, Python-based automation, and dashboarding. They have owned projects from stakeholder alignment and metric definition through rollout, with emphasis on reducing false positives, improving operational efficiency, and making analytics outputs easy for business teams to adopt.
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Key Strengths
- SQL-based data cleaning and validation for large transaction datasets
- Fraud detection analytics workflow automation in Python
- Reproducible analysis using Pandas, NumPy, scikit-learn, scripts, and notebooks
- End-to-end ownership of fraud analytics projects from problem framing to reporting
- Stakeholder alignment through regular cross-functional communication
- Metric design for fraud detection using precision, recall, and manual review reduction
- Retention metric design with thoughtful handling of edge cases
- Dashboard creation in Power BI and Tableau for stakeholder adoption
- Focus on reducing false positives and manual review effort
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