Li Yi

About Li Yi

I’m a PhD-trained data scientist who specializes in one thing: building scalable platforms that turn messy, novel, high-volume real-world data into decision-grade research and business assets. I’m at my best when the question is ambiguous, the data is unruly, and the stakes are real—taking work from “interesting idea” to an engineered system that delivers measurable impact.I’m currently a Clinical Data Scientist at Teladoc Health, supporting data science for chronic disease management and the data pipelines + performance measurement that power value-based care. My focus is building reliable, scalable analytics foundations that teams can trust—especially when reporting and outcomes matter.Before Teladoc, I’ve shipped across multiple data modalities:Built a proprietary SDOH risk-stratification asset by applying a pre-trained computer vision model to 350M+ street-view images and integrating outputs with claim, EHR, and decades of panel studies data.Architected a production-ready AWS platform for 10TB+ smartphone/wearable sensor data, cutting processing time by 90% and reducing defects by 30%.Applied rigorous observational methods (causal inference, survival modeling) to massive datasets, including 65M+ Medicare beneficiaries and 500K-person prospective cohorts, producing defensible, publishable insights.I care about building the “data engines” that accelerate R&D, strengthen measurement, reduce cost of care, and ultimately improve patient and population health outcomes. Always happy to connect with people working in digital health, RWE, and value-based care analytics.

Experience

1. Clinical Data Scientist Iii

   Teladoc Health

   Dec 2025 — Present

   Modernizing Teladoc’s performance-guarantee pipelines by migrating and refactoring legacy R into modular, high-performance, GitHub-versioned workflows with proactive monitoring- Productizing VBC analytics into reusable “building blocks” by standardizing cohort logic, outcome metrics, and reporting rules into scalable functions/workflows that adapt as measures and systems evolve- Delivering decision-grade clinical performance insights by validating metrics, diagnosing anomalies, and translating claims/admin data into clear actions for clinical, product, and client stakeholders.

Education

• UCL

  Master of Science - MS, Urban Policy

• University of Southern California

  Doctor of Philosophy - PhD, Population, Health and Place (Health Behavioral Research and Epidemiology focus)

• China Agricultural University

  Bachelor of Science - BS, Environmental Studies

• University of Pennsylvania

  Master of Science - MS, Urban Planning (Historic Preservation and Spatial Analytics focus)