Rohini Gandi

Conducted quantitative and statistical analysis on large clinical and pharmacy datasets and built a unified data warehouse using SQL and Python to improve extraction and reporting speed. Created Power BI dashboards with DAX KPI models for technical and non-technical stakeholders. Implemented SAS-based statistical validation and quality assurance to detect and correct data anomalies and support audit-ready reporting through metadata documentation and data governance. Led cross-functional reporting initiatives under agile workflows and translated stakeholder questions into analytics and predictive solutions.

Designed SQL-based ETL pipelines to consolidate high-volume transaction data, reducing latency and enabling near real-time statistical analysis for compliance and risk teams. Built Power BI scorecards and fraud-risk indicators and developed Python-based predictive models for anomaly detection. Delivered an end-to-end analytics platform combining SQL pipelines, Python processing, and Power BI dashboards to monitor transaction streams and reduce detection time. Maintained data governance, metadata documentation, and quality assurance standards for fraud-analytics reporting.

Extracted and analyzed large daily settlement datasets using SQL, improving data completeness and reducing manual reconciliation effort. Produced Power BI visual reports and dashboards to turn finance stakeholder questions into actionable insights. Automated data validation and quality checks with Python scripts to identify inconsistencies and prevent revenue leakage. Built an end-to-end payment settlement reporting system and collaborated with Finance and Operations to define requirements and deliver reliable, audit-ready reporting.