Naveen Kumar Eede

About Naveen Kumar Eede

I am a data-driven analytics professional with 6+ years of experience delivering enterprise-scale insights across financial services and healthcare environments. I specialize in transforming large, complex datasets into measurable business outcomes.At Wells Fargo, I support credit portfolios exceeding $4B in exposure, analyzing 80M+ monthly records to monitor loss emergence, delinquency trends, and payment behavior. By combining SQL, Python, AWS, and Power BI, I reduced refresh cycles from 6 hours to 75 minutes and helped improve forecast stability across 12 product segments.Previously at Humana, I built scalable Python pipelines processing 95M+ claim records per quarter and uncovered $3.8M in recoverable value through variance analysis and reconciliation workflows. My dashboards and KPI frameworks support 30+ stakeholders across risk, quality, and operations.Beyond reporting, I apply machine learning, NLP, and experimentation techniques to drive business outcomes — including influencing $1.3M in incremental payment recovery through A/B testing and deploying predictive models to prioritize high-risk members monthly.I bring a strong foundation in:• Advanced SQL & Data Modeling• Python-based automation & ML• Cloud analytics (AWS, Azure, Snowflake, Databricks)• Experimentation & KPI governance• Regulatory-compliant analytics (GLBA, HIPAA, BCBS 239, ECOA)I thrive at the intersection of analytics, engineering, and business strategy — translating data into clarity for executive decision-making.Open to Data Analyst, AI/ML, and Data Engineering roles across the U.S.

Experience

1. Data Analyst

   Wells Fargo

   Sep 2023 — Present · Dallas, TX, US

   Led enterprise credit analytics across 12 product segments supporting a $4B portfolio, analyzing 80M+ monthly records using Teradata SQL, Python, and AWS.• Reduced reporting refresh cycles from 6 hours to 75 minutes by redesigning SQL logic and optimizing Athena/PySpark processing workflows.• Designed and published an 18-KPI executive scorecard in Tableau and Power BI serving 25+ stakeholders across Cards and Digital.• Executed A/B testing across 2.1M customer touchpoints, driving $1.3M in incremental recovered payments in one quarter.• Built gradient boosting risk models in Python, reducing operational review queues by 4,500 accounts per month.• Implemented NLP-based theme detection on 120K+ monthly servicing notes, identifying 15 recurring issue drivers influencing policy updates.• Ensured regulatory compliance across GLBA, ECOA, and BCBS 239 by implementing masking, validation, and audit-ready documentation with zero material findings.

Education

• Jawaharlal Nehru Technological University Kakinada (JNTUK)

  Bachelor of Science - BS, Electronics and Communications Engineering

• Oklahoma Christian University

  Master of Science - MS, Science and Engineering