Pujit Koduru

Results-driven Senior Data Analyst with 6+ years of experience in data analysis, SQL analytics, ETL/ELT pipeline development, business intelligence, and machine learning. Proven track record building production data pipelines processing 10M+ records, deploying ML models at 85–92% accuracy, and architecting AWS cloud data platforms serving 200+ users. Delivered $5M+ in cost savings and $2M in fraud detection through advanced analytics, A/B testing, predictive modeling, and executive BI dashboards.

Skilled in Tableau, Power BI, Python, SQL, Snowflake, Databricks, and LLM/GenAI-powered automation.

Senior Data Analyst - Molina Healthcare - OH, USA

(2026-02)

• Healthcare Claims Analytics: Optimized provider network analysis using SQL and Python on 10M+ claims records (EPIC, Facets), improving network efficiency by 15%.
• BI Dashboard Development: Built Power BI dashboards visualizing unit cost trends across 500+ healthcare providers, enabling data-driven contract negotiations.
• Cloud Data Platform: Partnered with IT to implement an AWS data lake (S3, Glue), reducing data processing time by 30% and improving data accessibility for 50+ team members.
• Statistical Analysis: Conducted patient outcome analysis in SAS and Python, identifying key drivers that contributed to a 7% reduction in hospital readmission rates.
• Cost Savings Analysis: Analyzed contract structures via SQL analytics to surface $5M in cost-saving opportunities for negotiation cycles.
• Fraud Detection ML Model: Co-developed a machine learning classification model (Scikit-learn) with the Data Science team to detect fraudulent claims, flagging $2M in suspicious activity.
• Exploratory Data Analysis: Mined 3 years of historical claims data using Python (seaborn, matplotlib), uncovering trends that drove a 10% reduction in out-of-network utilization.
• Data Quality Framework: Implemented SQL data-quality checks and schema monitoring that reduced data errors by 25%, improving reliability of competitive unit-cost reporting.
• A/B Testing & Experimentation: Led A/B testing for new provider engagement strategies across 50,000 providers, identifying approaches that lifted participation by 22%.
• ETL Pipeline Design: Designed a Python ETL process integrating 5 disparate data sources, streamlining competitive-analysis workflows and reducing manual effort.
• Database Management: Built and maintained a relational database (SQL Server) tracking contract details for 10,000+ providers, improving data integrity by 40%.

Financial Data Analyst - Robert Half - CA, USA

(2025-04 - 2026-02)

• End-to-End ETL Pipelines: Developed and optimized data pipelines using Python, SQL, AWS, Workday, Kronos, and ERP systems, reducing manual processing effort by 60%.
• Executive BI Dashboards: Designed and maintained dashboards in Tableau and Power BI, providing leadership visibility into financial, payroll, workforce, and operational KPIs.
• Reporting Automation: Automated recurring financial and payroll workflows using Tableau Prep Builder, Power Automate, SQL, and Python, improving accuracy and turnaround time.
• Data Validation & Governance: Led data reconciliation and quality initiatives across Workday, Kronos, payroll, and financial systems, reducing discrepancies and strengthening governance.
• Enterprise System Migration (UAT/SIT): Supported PeopleSoft-to-Workday transformation through SIT/UAT testing, data validation, integration support, and business process analysis.
• Financial Analytics: Built workforce and financial analytics covering labor productivity, budget variance analysis, payroll operations, forecasting, and KPI reporting.
• LLM/AI Automation: Leveraged AI/LLM-assisted automation to streamline reporting and data classification, eliminating several hours of weekly manual effort.
• Cost Optimization: Contributed to financial optimization initiatives that improved cost visibility and supported approximately $800K in departmental overspend reduction.

Data Analyst - Cigna - OH, USA

(2023-01 - 2025-04)

• Python ETL Pipeline: Engineered a Python ETL pipeline unifying 5 data sources across 10M+ claims records with SQL validation at each stage, establishing a trusted single source of truth.
• AWS Data Lake Architecture: Architected an AWS data lake on S3 and Glue, cutting processing time 30%, lowering infrastructure costs, and scaling self-service analytics to 50+ analysts with governed RBAC.
• EPIC EHR Integration: Integrated and analyzed EPIC EHR data with claims and operational datasets to support patient outcome analysis and compliance reporting.
• Fraud Detection Model: Co-developed a Scikit-learn fraud-detection model using feature engineering and classification algorithms, flagging $2M in suspicious claims in production.
• A/B Testing Framework: Designed an A/B testing framework across 50,000+ providers using power analysis, hypothesis testing, and causal inference, delivering a 22% measurable lift.
• SQL Analytics & Cost Savings: Executed SQL analytics across 10M+ records to identify $5M+ in cost savings; built Power BI dashboards covering 500+ providers for contract negotiations.
• Data Quality Monitoring: Built a SQL data-quality framework with schema monitoring that caught a silent ERP categorization change, resolved root cause in 4 hours, and added permanent guardrails.
• Real-Time Streaming: Deployed Amazon Kinesis real-time streaming, upgrading data freshness from daily batch to near-real-time and expanding operational analytics capabilities.
• LLM API Integration: Integrated LLM APIs for automated data classification, reducing manual categorization effort and accelerating insight delivery across Finance and Operations.

Data Engineer & Analyst - Mindlabz Technologies - India

(2019-01 - 2021-12)

• Clinical Data Lake (AWS): Architected a 7TB clinical data lake on AWS S3 and Glue with Kinesis real-time streaming, implementing HIPAA-compliant RBAC and full data lineage for 200+ users.
• Python Data Pipelines: Built Python pipelines preprocessing 10M+ patient records with cleaning, normalization, and automated quality checks, establishing enterprise data standards.
• Data Warehouse Design: Designed a star-schema dimensional data warehouse, optimizing query performance, standardizing KPI definitions, and enforcing data-governance policies organization-wide.
• Predictive ML Models: Developed a predictive readmission ML model at 85% accuracy (reducing readmissions 15%) and an imaging classifier at 92% detection accuracy, both deployed to production.
• BI Dashboards & Training: Built Power BI and Tableau dashboards across 50+ departments and led training programs enabling 200+ non-technical users to operate self-service analytics.
• NLP & Sentiment Analysis: Applied NLP and sentiment analysis on patient feedback, identifying dissatisfaction drivers tied to a 20% improvement in patient satisfaction scores.
• AWS Glue ETL Orchestration: Orchestrated AWS Glue ETL jobs with automated scheduling, eliminating manual pipeline maintenance and reducing data latency.
• Hybrid Data Architecture: Implemented SSIS integration pipelines connecting on-premise systems to the AWS data lake, enabling a hybrid data architecture and unified reporting.

Master of Science - Information Systems - Cleveland State University (2022-01 - 2023-08)

Bachelor of Technology - Mechanical Engineering - Sreenidhi Institute of Science and Technology (2016-09 - 2020-07)