Pranav Varma
(JPMC)
(Amazon, JPMC)
Amazon
Barclays
Fortune 500 Companies Served
Driving Data-Driven Decisions Across Fortune 500 Companies
I'm a results-oriented data analytics professional with 5+ years of experience transforming complex datasets into actionable business insights. Currently serving as Sr. Associate in Quant Analytics at J.P. Morgan Chase, I specialize in applying data analytics and machine learning, and building scalable ETL pipelines to drive measurable business impact.
J.P. Morgan Chase
Led customer outreach optimization initiatives, achieving a 10% monthly increase in identity validation rates through advanced analytics.
Amazon
Built comprehensive ML attribution model reporting that analyzed marketing spend allocation, resulting in a 10% reduction in overall marketing costs while maintaining customer acquisition targets across various channels.
Barclays
Implemented advanced SQL optimization techniques and automated ETL processes, significantly improving data pipeline efficiency and reducing processing time by 40%.
Deutsche Bank
Developed comprehensive UI automation solutions that reduced manual operational effort by 70%, streamlining critical business processes and improving team productivity.
Carnegie Mellon University
Masters in Information Systems (Business Intelligence & Data Analytics)
Technical Arsenal
Comprehensive technical stack showcasing versatility across data science tools and modern technologies
Professional Certifications
Certified in Advanced SQL, Machine Learning, and Business Intelligence
Programming Languages
Data Science & ML
Visualization & BI
Big Data & Cloud
Database & Tools
Projects That Drive Results
Customer Segmentation Waterfall
Leveraged internal and external data sources to help tax team reduce costs by 22% annually through advanced customer segmentation analysis and predictive modeling.
Media Mix Model Attribution
Built ML model comparison framework reducing marketing spend by 10%. Created Tableau dashboards saving 80 hours annually through automated reporting.
Loan Investment Recommender
Implemented MLPerceptron, Spline, and Gaussian NB models for LendingClub data analysis with feature engineering optimization achieving 95% accuracy.
Risk Reporting Automation
Automated UI testing for 6 applications, reducing manual effort by 70% and testing time by 45% through comprehensive test automation framework.
Ready to Transform Your Data into Insights?
I'm currently open to new opportunities in data science and data engineering. Let's discuss how I can help drive data-driven growth for your organization.