Ylan Kazi
  • Male
  • Minneapolis, Minnesota
  • United States
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Short Bio:
Ylan Kazi is the Director of Data Science and Machine Learning for UnitedHealthcare, where he leads a team of data scientists that apply machine learning to challenging healthcare business problems. In his role, he creates the strategy for how to apply machine learning to Medicare Part D, specifically for medication adherence and targeted member interventions. He guides his team on the creation of novel machine learning solutions for healthcare that will improve health outcomes for patients and increase ROI for the organization.

Ylan has held different analytical leadership positions in the past. These positions included Cerner, where he served as healthcare delivery consultant; Accretive Health, where he served as a healthcare management consultant; and at Target, where he served as a healthcare manager.

Ylan’s focus has always been leading analytical teams and helping organizations find the most value from their analytics. As analytics have evolved to using machine learning and deep learning, Ylan has stayed up-to-date on these trends, and experimented with ways to implement them for organizations. He blogs about machine learning at ylankazi.com as well as for Data Science Central. Ylan has a strong interest in natural language processing and how to use it to benefit patients and healthcare stakeholders.

He earned a Bachelor’s degree in Philosophy from Carthage College and a Master’s degree in Healthcare Administration from the University of Minnesota.
UnitedHealth Group
Job Title:
Director, Data Science and Machine Learning
Executive Management
LinkedIn Profile:

Ylan Kazi's Blog

Go Ahead and Automate Jobs

Posted on May 27, 2018 at 11:30am 2 Comments

Machine learning has the ability to automate a lot of jobs in the future. It is very easy to talk about this automation when it isn't your job that will be automated. But the scary part is that there are a lot of highly skilled jobs that will also face some type of automation in the future as well. When you are talking about your own job potentially being automated, it becomes less abstract and more real. It is very easy to say go ahead and automate jobs, until it is your own that is being…


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