Alyssa Feldman

Principal Statistician, Data Science And Predictive Analytics @ WPS Health Solutions

About Alyssa Feldman

Alyssa Feldman is a Principal Statistician specializing in Data Science and Predictive Analytics at WPS Health Solutions, where she leads a team focused on advanced analytics and forecasting in Medicare data. She holds a Master's degree from Brown University and has a diverse educational background in psychology and chemistry from Pace University, as well as a brief study in Chinese medicine at Hong Kong Baptist University.

Work at WPS Health Solutions

Alyssa Feldman has been employed at WPS Health Solutions since 2016, where she serves as the Principal Statistician in the Data Science and Predictive Analytics department. In this role, she leads an analytic team that focuses on advanced analytics and forecasting specifically related to Medicare data. Her contributions are integral to the organization's efforts in utilizing data for improved decision-making and strategic planning.

Education and Expertise

Alyssa Feldman holds a Bachelor of Arts degree from Pace University, where she studied Psychology and Chemistry from 2008 to 2012. She furthered her education at Brown University, earning a Master of Science degree from 2012 to 2014. Her research at Brown University concentrated on spatial and temporal trends of global infectious disease outbreaks. Additionally, she studied Chinese Medicine at Hong Kong Baptist University for one year in 2009-2010.

Background

Before her current role at WPS Health Solutions, Alyssa Feldman worked as a Senior Statistician at the same organization from 2015 to 2016. Prior to that, she was a Technical Analyst at Epic for six months in 2014-2015. Her early career included a position as a Research Assistant at Brown University from 2013 to 2014, where she contributed to various research projects.

Research Focus

During her time at Brown University, Alyssa Feldman's research was centered on analyzing spatial and temporal trends of global infectious disease outbreaks. This work involved examining patterns and data related to infectious diseases, contributing to the understanding of their spread and impact on public health.

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