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Summary

Business Analyst with expertise in data analysis, enterprise data warehouse system (EDW), machine learning, and AI-powered solutions. Achievements include a 40% improvement in analysis accuracy, 50% reduction in processing time, and 30% boost in grant relevancy. Skilled in building data pipelines, deploying interactive dashboards, and delivering actionable insights. Enjoys FPS gaming and travel for fun and always seeking adventures.

Work Experience

2024-08Present

Data Analyst

Santech Solutions, Princeton, NJ
  • Streamlined contract workflows in the healthcare sector by developing iSmart, an AI-powered healthcare tool integrated with iNetwork for automated contract analysis, summarization, clause extraction, and new contract generation.
  • Improved Contract analysis accuracy and decreased manual review time by implementing machine learning models and vector storage systems automating contract review processes and reducing human errors.
  • Delivered actionable insights and enhanced operational efficiency by addressing unorganized contract management, enabling faster decision-making and optimizing resource allocation through AI-driven automation.
2024-012024-05

Business Analyst

Discovery Partner Institute (DPI), Champaign, IL
  • Increased grant relevancy and effectiveness by 30% by leading a 9-member team to develop an AI and LLM-powered tool for project and grant tracking at DPI, leveraging AI algorithms and Python web scraping to streamline workflows.
  • Enhanced data retrieval accuracy by 40% and halved processing time by designing and deploying a comprehensive data extraction and summarization system using Azure Chat OpenAI, advanced NLP models, and PDF extraction.
2021-052022-11

Software Engineer/Analyst

Capgemini, Bangalore, India
  • Enhanced data-driven decision-making by developing a new feature for the devlink project, leveraging Tableau and Excel to analyze productivity metrics, perform impact analysis, and identify bottlenecks in workflows, improving team efficiency.
  • Reduced system errors by 30% through advanced data debugging techniques for UICC driver and NVM issues, using Lauterbach/JTAG debugger and conducting statistical analysis to validate the improvements and ensure system reliability.
  • Achieved a 95% resolution rate by collaborating with cross-functional teams to analyze and address recurring issues in memory shared systems, SIM drivers, and I2C components, utilizing root cause analysis and data insights to develop long-term solutions.

Education

2023-082024-05

Master’s in Business Analytics

University of Illinois Urbana-Champaign, Champaign, IL

GPA: 3.85/4.00

2017-072021-05

Bachelor of Technology in Electronics and Communication Engineering

SRM Institute of Science and Technology, Chennai, India

GPA: 7.61/10

Academic Projects

Cloud-Optimized Data Ecosystem Project Integration

GitHub

Developed cloud-based MongoDB clusters for secure data management and integrated Yelp and real-time NFT sales data using Python. Enhanced decision-making by 30% through KNIME workflows analyzing 200+ restaurants and thousands of NFT transactions.

Real-Time NBA Data Analytics Pipeline

GitHub

Enhanced real-time NBA game analysis and decision-making by developing a data pipeline with Apache Kafka, Apache Spark, InfluxDB, and Grafana for efficient handling of live game statistics and player metrics. Boosted fan engagement by creating interactive Grafana dashboards with real-time updates and visual insights.

Statistical Modeling for Property Valuation

GitHub

Improved dataset compatibility by addressing missing values, outliers, and inconsistencies and identifying key factors influencing house sale prices through statistical analysis. Achieved 92% accuracy in price prediction using Lasso regression.