Simin (Sandy) Farr, PhD
About Simin (Sandy) Farr, PhD
Simin (Sandy) Farr, PhD, is the Senior Manager of Data Science at Fannie Mae in the Washington D.C. Metro Area. She has a background in advanced research, having worked at NASA Goddard Space Flight Center, University of Maryland, and Washington University in St. Louis.
Current Role at Fannie Mae
Simin (Sandy) Farr, PhD, serves as the Senior Manager of Data Science at Fannie Mae, located in the Washington D.C. Metro Area. In this capacity, she has been leading data science initiatives since August 2018. She is responsible for driving data-driven decision-making within the organization, utilizing her extensive experience and expertise in the field.
Experience at NASA Goddard Space Flight Center
From 2014 to 2018, Simin (Sandy) Farr worked as a Research Scientist at NASA Goddard Space Flight Center in Greenbelt, MD. During her four years at NASA, she was involved in advanced research projects, contributing significantly to the center’s scientific endeavors. Her role required high-level analytical skills and a deep understanding of complex scientific concepts.
Academic Research at University of Maryland
Simin (Sandy) Farr served as a Postdoctoral Research Associate at the University of Maryland from 2012 to 2014. During her two-year tenure at College Park, MD, she contributed to multiple academic research projects, showcasing her strong background in scientific inquiry and research methodologies.
Early Research Experience at Washington University in St. Louis
Simin (Sandy) Farr’s early research experience includes a five-year period (2007-2012) as a Research Assistant at Washington University in St. Louis. During this time, she gained extensive experience in research, which laid a solid foundation for her subsequent roles. Her work primarily focused on physics, which was also the subject of her doctoral studies.
Educational Background
Simin (Sandy) Farr holds a PhD in Physics from Washington University in St. Louis, where she studied from 2007 to 2012. Her doctoral studies provided her with a robust foundation in scientific research and data analysis, equipping her with the skills necessary for her subsequent roles in both academic and applied research settings.