I am an award-winning data scientist and analytics expert with board-certification in informatics and over 10 years experience in IT and data tech. I am passionate about answering complex problems by developing knowledge tools using AI and advanced analytic methods, for immediate application. I have led numerous enterprise-scale data science and analytics projects. I am proficient in Python, R, SQL, Tableau, and Stata. Among my accomplishments, in 2019, I published the first systematic review of data science models vs. traditional tools predicting deterioration risk, and I received the 2019 UCSF Distinguished Dissertation Award.
Key interests and expertise: AI and machine learning applications, predictive analytics; risk-adjustment; statistical modeling; business decision support; economic evaluations and business case development; quantitative research.
“During my time as Dean at UCSF, Daniel was a rising star in the field of data science/big data, and I was so pleased to see his selection for Distinguished Dissertation Award.
Dr. Linnen is an exceptional contributor and solid programmer. He would be a great addition to any data science team.”
— David Vlahov, PhD
Professor at Yale University
Former Dean at UCSF
“I’ve worked with Dr. Linnen directly on different advanced analytics projects and I cannot recommend his character or capabilities highly enough!
He has technical skills that would be an asset to any team”
— Austin Powell
Senior Data Scientist at Stanford Children’s Health
“Daniel is a passionate data scientist and quantitative researcher. As his qualifying exam chair and dissertation committee member, Daniel impressed me with his desire to write his own statistical programs, his deep subject matter expertise in data science, and use of machine learning to optimize operations”
– Xiao Hu, PhD
Distinguished Professor at Duke University
Former faculty at UCSF Bakar Computational Health Sciences Institute