Interwell Health
Daniel Chen is an experienced professional in machine learning and bioinformatics, currently serving as a Machine Learning Engineer at Interwell Health. With a background that includes roles at Wurl and Gilead Sciences, Daniel has led the development of advanced NLP models and architected a cost-saving data engineering stack using Kubernetes and Airflow. Experience spans various positions, including Scientist at Roche and freelance web developer, demonstrating expertise in data analysis, project leadership, and technology integration. Daniel holds an MBA from USC Marshall School of Business, a Master’s degree in Data Science from Harvard Extension School, and a Bachelor's degree in Biotechnology from the University of California, Davis.
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Interwell Health
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InterWell Health is a national physician-centric partnership between Fresenius Medical Care North America. It combines the expertise of a diverse and preeminent group of nephrology practices with the experience of FMCNA and aims to advance value-based contracting models that are attractive to all renal providers, payors, and patients by drivingbetter clinical outcomes at lower costs.