Naga VA Kumar G

Experience

• 

  BYJU'S

  Jul 2018 - Aug 2019

  Data Analyst

  Enhanced LMS Adoption by 20%: Supported the team lead in analyzing LMS usage data using Excel and SQL, identifying key issues, and implementing solutions that increased adoption by 20% within a week.Data Maintenance & Training Support: Collaborated with a 15-member team to maintain and update data in Google Sheets, ensuring accuracy and accessibility. Assisted in developing training solutions based on data insights to improve team performance.Interactive Dashboard Development: Contributed to the creation of an interactive daily productivity dashboard on Looker Studio, providing dynamic reports to the Senior Manager and enabling data-driven decision-making.LMS Administration Support: Acted as a key support member for the LMS platform, serving over 2,400 employees. Conducted data preparation, cleaning, and analysis using Excel and SQL, generating pivot reports and charts at both subject and individual levels to support strategic decisions.Cross-Functional Collaboration: Worked closely with the team lead and other stakeholders to ensure alignment between LMS functionality and employee needs, contributing to the platform's successful adoption and utilization. Show less

• 

  Greymetre Consultants Pvt Ltd

  Aug 2019 - Dec 2022

  Chronic Disease Management: Led a data analytics initiative for diabetes and hypertension, building a predictive model with Python and SparkML, reducing hospitalizations by 30%.Insurance Claims Analytics: Designed Power BI dashboards to monitor KPIs like claims approval rates and fraud detection, improving decision-making by 25% and reducing fraudulent payouts by 15%.Agile Project Management: Managed projects using JIRA and Confluence, conducting daily stand-ups, sprint planning, and retrospectives to ensure timely delivery.Data Integration & Automation: Automated data extraction and transformation using Azure Data Factory and Databricks, reducing manual effort by 50% and ensuring real-time dashboard updates.Cross-Functional Leadership: Led teams of data scientists, clinicians, and IT specialists, aligning projects with organizational goals and presenting insights to stakeholders for buy-in. Show less Designed and Deployed Power BI Dashboards: Created interactive dashboards to monitor KPIs such as claims approval rates, average processing time, and fraud detection rates. Used DAX functions for advanced calculations, improving decision-making accuracy by 25% and enabling real-time tracking of claims performance.Developed Fraud Detection Model: Built a machine learning model using Python and Apache Spark on Databricks to identify fraudulent claims. Analyzed historical data to detect patterns and anomalies, reducing fraudulent payouts by 15%. Integrated the model into Power BI for real-time monitoring.Automated Data Integration with GCP: Automated extraction and transformation of claims data from multiple sources (e.g., policy databases, customer submissions) using Google BigQuery and Apache Airflow. Built scalable ETL pipelines in Databricks, reducing manual data entry by 50% and ensuring timely updates to dashboards.Implemented Real-Time Streaming Analytics: Used Databricks Structured Streaming to monitor incoming claims data in real-time. Reduced latency in dashboard updates, enabling faster response to anomalies and improving operational efficiency by 10%.Data Wrangling and Quality Assurance:Cleansed and transformed data using Power Query and Delta Lake, reducing preparation time by 40%. Show less

  • Project Manager Data Analytics

    Jan 2021 - Dec 2022

  • Business Analyst

    Aug 2019 - Jan 2021
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  PragmaticITInc

  Feb 2024 - now

  Data Analyst

  SQL-Driven Data Analysis: Wrote complex SQL queries to extract, transform, and analyze data from multiple sources, improving query performance by 35% through indexing, partitioning, and caching.Azure Data Integration: Designed and implemented scalable ETL pipelines using Azure Data Factory and Databricks, integrating data from 10+ sources and reducing manual effort by 40%.Machine Learning Models: Built and deployed machine learning models using Python and SparkML to predict customer churn and fraud, improving decision-making accuracy by 25%.Data Visualization with Power BI: Designed and deployed interactive Power BI dashboards to visualize KPIs such as sales performance, operational efficiency, and customer satisfaction, enabling real-time decision-making.Real-Time Analytics with Azure: Implemented real-time streaming analytics using Azure Databricks and Delta Lake, reducing latency in dashboard updates and improving operational efficiency by 10% Show less