Hardik Pawankumar

Built ETL pipelines using Microsoft SQL Server and Alteryx for Medicare claims analysis, using Python (Pandas, NumPy) to detect fraudulent claim patterns and billing anomalies across datasets, identifying ~$1M in potential cost savings. Designed and maintained Power BI dashboards for provider metrics (readmission rates, patient outcomes, treatment costs) using DAX and SQL, enabling better network optimization. Collaborated in Agile to develop a claims trend analysis system in Power BI for real-time monitoring of outpatient, inpatient, and prescription patterns. Implemented automated data validation and standardized diagnosis codes using Alteryx with custom Python scripts, reducing data discrepancies by 40% and improving compliance reporting accuracy. Supported migration of claims data to Google Cloud Platform (BigQuery), validated accuracy during transition, and analyzed provider performance (patient satisfaction, recovery times, cost metrics) contributing to a 25% reduction in network

Performed data quality assurance using SQL and Python for cleansing customer subscription datasets, reducing error rates by 18% for a Customer Churn Prediction effort. Developed a predictive model in Python and BigQuery to identify high-risk customer segments on Google Cloud, improving retention by 12% through targeted strategies. Created an executive IT Services Revenue & Customer Growth dashboard in Tableau, visualizing subscription trends and financial KPIs to support resource allocation. Analyzed user engagement metrics in an Agile environment and conducted A/B testing on pricing models to inform feature prioritization and marketing strategy adjustments. Migrated legacy data to cloud infrastructure and maintained pipelines to AWS Redshift for KPI dashboards, using Git for version control and ensuring compliance with data security protocols.