Roland Jeannier
About Roland Jeannier
Roland Jeannier is a Senior Data Science Associate at Fannie Mae with a background in physics and extensive experience in data science and software development.
Current Role at Fannie Mae
Roland Jeannier currently holds the position of Senior Data Science Associate at Fannie Mae. In this role, he focuses on developing predictive models to optimize mortgage underwriting processes. His expertise in data science underpins significant contributions to Fannie Mae's financial services.
Previous Experience at Fannie Mae
Before becoming a Senior Data Science Associate, Roland Jeannier served as a Data Science Associate at Fannie Mae from 2018 to 2021 in Washington, D.C. His earlier role included responsibilities as a Design Strategist for 7 months from 2017 to 2018 in the Washington, D.C. Metro Area. During his tenure, he worked on various strategic design and data science projects.
Past Roles in Technology and Data Science
Roland Jeannier has an extensive background in technology and data science. From 2014 to 2017, he worked as a Software Developer/Consultant at Sila Solutions Group in Arlington, VA. He also held a position as a Junior Java Developer at SAIC from 2013 to 2014 in McLean, VA. His early career included a stint as a Research Assistant at the University of Maryland from 2011 to 2013 in College Park, Maryland. Additionally, he enhanced his data science skills as a student at General Assembly in 2017.
Educational Background in Physics
Roland Jeannier has a strong academic background in physics. He earned a B.S. in Physics from the University of Maryland between 2009 and 2012. Prior to that, he studied Physics at Loyola University Maryland for one year from 2008 to 2009. He completed his high school education at Mount Saint Joseph High School, graduating with a diploma in 2008.
Professional Achievements and Contributions
Roland Jeannier has several notable accomplishments in his career. He presented research findings at the 2022 Data Science Conference in Washington, D.C., and contributed to a white paper on the impact of machine learning in financial services. Additionally, he volunteers as a mentor for aspiring data scientists through the Data Science for Social Good initiative. He holds a certification in Machine Learning from Coursera, further showcasing his dedication to continuous learning and professional development.