Bharath Jagarlamudi

About Bharath Jagarlamudi

I am a Data Analyst with over 3 years of experience building data-driven solutions across financial services and healthcare analytics. My work focuses on transforming large-scale datasets into actionable insights that support strategic decision-making, forecasting accuracy, and operational efficiency. At S&P Global, I analyze millions of financial and market records to improve revenue forecasting and build predictive models that support product and market strategy. I design scalable ELT pipelines using Airflow, dbt, and BigQuery while developing Tableau and Power BI dashboards that enable executives and product teams to monitor key performance metrics in real time.Previously at Omega Healthcare, I worked extensively with Medicare and Medicaid claims data to identify irregular billing patterns, detect fraud risks, and improve compliance monitoring. I developed anomaly detection models, automated ETL workflows, and built analytics dashboards that strengthened fraud detection and helped recover significant overpayments.My technical expertise includes SQL, Python, BigQuery, Airflow, dbt, SAS, Tableau, and Power BI. I specialize in building reliable data pipelines, conducting statistical experimentation, and developing KPI frameworks that bridge the gap between technical data systems and business strategy.I am particularly interested in roles where I can contribute to data-driven decision making, scalable analytics infrastructure, and advanced forecasting or fraud detection initiatives.Core areas of focus: • Data Analytics & Business Intelligence • Financial & Healthcare Data Analysis • Predictive Modeling & Forecasting • Fraud Detection & Risk Analytics • Data Pipelines & ETL Automation

Experience

1. Data Analyst

   S&P Global

   Feb 2025 — Present · New York, NY, US

   Analyze large-scale financial and market datasets using SQL and BigQuery to improve revenue and market forecasting accuracy by 28%.• Develop predictive models and regression frameworks in Python to strengthen forecast reliability across product lines.• Architect and maintain Airflow-orchestrated dbt ELT pipelines with automated data quality checks and incremental data modeling, reducing data refresh cycles by 45%.• Design KPI frameworks and enterprise dashboards in Tableau and Power BI to support executive reporting and cross-functional decision making.• Optimize BigQuery transformations through partitioning and performance tuning, reducing query execution time by 40% and lowering warehouse compute costs by 25%.• Lead A/B experimentation and hypothesis testing initiatives on pricing and acquisition data, improving conversion performance by 15%.

Education

• New York Institute of Technology

  Master of Science - MS, Computer Science

• Chennai Institute of Technology

  Bachelor of Engineering, Computer Engineering

  2019 — 2023

• Chennai Institute of Technology

  Bachelor of Engineering - BE, Computer science and engineering

• New York Institute of Technology

  Master's Degree, Computational Science

  2024