Keese Phillips

About Keese Phillips

I am an Analytics Engineer focused on building high-performance data foundations that drive product-level decisions. My background bridges the gap between Computer Science and Finance, allowing me to engineer scalable pipelines while maintaining a deep understanding of business P&L.Currently, at PNC, I architect automated data systems processing over 200M+ records daily using Spark and Python. I specialize in- Scalable Infrastructure: Designing robust ETL/ELT pipelines for massive dataset- Data Observability: Implementing automated monitoring to ensure data integrity and model reliability- Cross-Functional Impact: Partnering with stakeholders to transform raw data into actionable product insights.With a Master of Engineering in AI from Duke University, I am passionate about applying machine learning and low-latency programming (C++/Python) to solve complex data challenges at scale.

Experience

1. Business Analytics Consultant Senior

   PNC

   Mar 2025 — Present

   Decision Science and Analytics Credit and Operational Intelligence - Data Engineering at Scale: Engineered automated risk monitoring pipelines using Spark and Python to process 200M+ records- Data Reliability: Implemented alerting protocols for model drift to maintain high data integrity across legacy and new systems- Performance Optimization: Built high-efficiency big data tables to report on payment platforms, managing analysis for millions of monthly transactions.

Education

• University of Georgia - Franklin College of Arts and Sciences

  Bachelor of Science - BS, Computer Science

• University of Georgia - Terry College of Business

  Bachelor of Business Administration - BBA, Finance

• Duke University Pratt School of Engineering

  Master of Engineering - MEng, Artificial Intelligence