Keunyoung Young Yoon

About Keunyoung Young Yoon

Portfolio: youngyoon.meI spent 5 years running data analytics for FIFA Online 4, one of Korea’s largest online games by active user base, building automated production queries and visualizations, optimizing monetization, and driving 10% YoY revenue growth.Now I\'m applying that same analytical rigor to healthcare data systems.At GSK-ViiV Healthcare, as an intern and co-op, I design pharmaceutical data pipelines that ensure accuracy and compliance across specialty pharmacy datasets. I also build ad hoc business reports that support sales decision-making. My experience chasing down every data discrepancy in high-stakes revenue operations translates directly here. At scale, data quality isn\'t just about clean numbers. It\'s about decisions that affect patient outcomes.Currently researching fairness in deep learning-based mortality prediction models at Emory (manuscript in progress) and NLP-based dementia detection at Rutgers. Finishing my MS in Data Science at Stony Brook.Looking for roles where big data analytics & engineering meets healthcare impact: pharmaceutical analytics (commercial/clinical), healthcare data platforms, or clinical informatics.

Experience

1. Data Strategy and Operations Academic Year Co-op

   GSK

   Sep 2025 — Present · NY, US

   Developed automated data profiling pipelines using PySpark and SQL, processing patient-level SP data (hub enrollment, dispense, adherence) across 10+ specialty pharmacy datasets and 130+ territories—supplemented by IQVIA for subnational-level validation and market consistency- Documented 3+ end-to-end data flow diagrams in Visio to visualize multi-layer data architecture (landing, enriched, semantic layers), aligning with data governance, monitoring, and compliance standards- Refined Power BI dashboards with DAX measures to surface specialty pharmacy patient journey and commercial performance KPIs, improving C-suite and commercial leadership visibility into brand performance and SP channel dynamics- Automated recurring commercial reporting workflows via Power Automate and Python, reducing report turnaround from 2 days to ~1 hour (95% reduction), enabling timely insights for sales force and market access teams- Leveraged statistical methods (Z-score, t-tests, correlation analysis) on pharmacy and prescription datasets to validate data integrity, detect anomalies, and assess commercial strategy impact.

Education

• Sogang University

  Bachelor's degree, Political Science / Business Administration

• Korea National Open University

  Bachelor of Science, Data Science and Statistics

• Stony Brook University

  Master's degree, Data Science