Sungmin Kim

Building scalable data pipelines and AI-powered systems that drive precision medicine and clinical data intelligence at a leading AI-driven healthcare company.

• Design and maintain high-throughput ETL pipelines processing clinical genomics data at scale
• Integrate LLM-based agents for automated data quality and enrichment workflows
• Lead cross-functional collaboration with ML engineers, data scientists, and clinical scientists
• Architect and optimize cloud infrastructure on AWS for cost efficiency and performance
• Mentor junior engineers and drive best practices in code review and system design

Designed and delivered end-to-end data engineering solutions for enterprise clients, specializing in cloud data pipelines and analytics infrastructure.

• Built and maintained scalable ETL pipelines ingesting large volumes of client data into cloud warehouses
• Developed data models and transformation logic using Python and SQL for downstream analytics
• Collaborated with analytics and product teams to deliver data-driven features on schedule
• Automated data quality checks and monitoring to ensure pipeline reliability

Applied machine learning and statistical modeling to extract actionable insights from large datasets, supporting product and business decision-making.

• Developed and deployed ML models for customer segmentation and predictive analytics
• Built data pipelines and feature engineering workflows to support model training and evaluation
• Communicated findings to non-technical stakeholders through dashboards and reports
• Collaborated with engineering teams to productionize models into core product features

Contributed to analytics projects and exploratory data analysis for enterprise clients during a focused summer internship.

• Conducted exploratory data analysis and statistical modeling on client datasets
• Built interactive visualizations using Tableau and D3.js for executive reporting
• Supported senior data scientists in model development and validation

Contributed to backend software development for IoT connectivity products supporting industrial and commercial deployments worldwide.

• Developed and maintained Java-based backend services for IoT device management
• Implemented data collection and monitoring pipelines for connected device fleets
• Improved system reliability through automated testing and thorough code reviews