B. PAVANI
Data Analyst • Los Angeles, CA, USA • b**********@gmail.com • +19******232 • drivetube.ai/•••••
Professional Summary
Data Analyst with 4+ years of experience transforming complex healthcare and financial data into actionable insights. Skilled in SQL, Python, Power BI and Tableau; built predictive models and automated ETL to drive $2M annual savings and reduce hospital readmissions by 20%. Experienced in exploratory data analysis, time-series forecasting, KPI reporting, and partnering with clinical, finance, and engineering teams to deliver HIPAA-compliant analytics in Agile environments.
Technical Skills
Programming Languages: Python,R
Frameworks and Libraries: Scikit-learn
Databases: SQL,PostgreSQL,MySQL,SQL Server,Amazon Redshift,Snowflake
Cloud and DevOps: AWS,Azure,Docker
Data and Analytics: Power BI,Tableau,Excel,XGBoost,Prophet,Time Series Forecasting,Anomaly Detection
Tools and Methodologies: Git
ETL & Orchestration: Apache Airflow,AWS Glue,SSIS,Alteryx,Python ETL scripts
Work Experience
Optum
Los Angeles, CA
Data Analyst
Feb 2024 – Present
Healthcare analytics supporting Medicaid population management and clinical/finance stakeholders to reduce utilization and cost while maintaining HIPAA compliance.
Tech Stack: Python, XGBoost, Scikit-learn, SQL, PostgreSQL, SQL Server, Power BI, Excel VBA, AWS S3, Amazon Redshift, AWS Lambda, Jira, Git
- Developed predictive models using Python and XGBoost to forecast Medicaid member utilization across 500,000+ patient records; achieved 87% accuracy and contributed to a 20% reduction in 30-day hospital readmissions within 12 months.
- Designed and published Power BI dashboards tracking patient risk, utilization and cost metrics; enabled executive decisions that produced $2M in annual savings.
- Performed exploratory data analysis on large-scale EHR and claims datasets to surface trends and outliers, translating findings into prioritized care management interventions for clinical and finance teams.
- Optimized complex SQL queries spanning 400+ tables, reducing average execution time from 45s to under 8s and improving reporting accuracy by 30%.
- Automated data validation and ETL workflows using Python and Excel VBA, cutting manual reporting errors by 50% and improving processing throughput by 60%.
- Built automated KPI reports and executive scorecards to monitor operational performance, saving 12+ hours per month and ensuring all analytics adhered to HIPAA controls.
Virtusa
India
Data Engineer & Analyst
Dec 2022 – Jul 2023
Consulting and data engineering for enterprise analytics, migrating on-prem warehouses to cloud and building production ETL pipelines for client BI and reporting needs.
Tech Stack: Python, PostgreSQL, MySQL, SQL Server, Apache Airflow, Docker, AWS S3, EC2, Jira, Confluence, Git
- Managed and tuned PostgreSQL databases for large analytics workloads, improving query performance by 35% while supporting 50+ concurrent analytics users.
- Built end-to-end ETL pipelines with Python and Apache Airflow integrating 12+ source systems; reduced data latency from 6 hours to 90 minutes for downstream reporting.
- Implemented automated data quality monitoring and root-cause analysis, cutting issue detection time from 45 minutes to 12 minutes and improving pipeline reliability.
- Automated SQL migration and data seeding processes to enforce consistent schemas across environments, reducing deployment failures by 40%.
- Collaborated with data architects, business analysts and product managers to deliver 15+ releases with zero critical post-production defects.
- Containerized ETL workloads with Docker and integrated pipelines with AWS S3 and EC2 to improve deployment speed and operational stability.
Virtusa
India
Data Analyst Intern
Jan 2022 – Dec 2022
Financial analytics internship creating forecasting models and dashboards to support budgeting and spending analysis for enterprise finance teams.
Tech Stack: Python, Pandas, NumPy, Scikit-learn, Prophet, PostgreSQL, MySQL, Tableau, Alteryx, Apache Airflow, UiPath, Excel VBA, Git
- Developed Tableau dashboards to track financial KPIs, budget variance, forecast accuracy and spending trends, reducing monthly reporting time by 40%.
- Built time-series forecasting models using Python on 5+ years of financial data, improving forecast accuracy to within 3% of actuals and reducing budgeting errors by 30%.
- Wrote and optimized advanced SQL queries across PostgreSQL and MySQL databases, supporting month-end financial reporting with 100% data accuracy.
- Applied anomaly detection using Isolation Forest to identify irregular transactions, improving data quality by 25% and preventing $500K in potential discrepancies.
- Automated recurring reporting workflows using Tableau, SQL, Excel and UiPath, reducing manual effort by 50% and saving 20+ hours per month.
- Performed feature engineering and exploratory data analysis to prepare datasets for forecasting and anomaly detection, standardizing inputs for BI consumption.
Git KEY PROJECTS Healthcare
Education
University of Central Missouri
Master of Science in Computer Information Systems • Warrensburg, MO
Gudlavalleru Engineering College
Bachelor of Technology in Electronics & Communication Engineering • India
Certifications
AWS Certified Solutions Architect – Associate — Amazon Web Services
Microsoft Certified: Azure Fundamentals (AZ-900) — Microsoft
Certified Python Programmer
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