Sam Dworetzky
About Sam Dworetzky
Sam Dworetzky is a Data Scientist at PRA Group, specializing in machine learning and predictive modeling to enhance customer behavior insights and business strategies. He holds a Bachelor of Science in Mathematics from Virginia Commonwealth University and a Master of Science in Mathematics from Boise State University.
Work at PRA Group
Sam Dworetzky has been employed at PRA Group (Nasdaq: PRAA) since 2018, currently holding the position of Data Scientist. His role involves utilizing machine learning to develop predictive models that provide insights into customer behavior and optimize business strategies. Prior to this position, he worked as a Data Modeler Intern at PRA Group for two months in 2018, where he gained initial experience in data modeling. His contributions focus on improving business outcomes by optimizing payer channels and customer touch points.
Education and Expertise
Sam Dworetzky earned a Bachelor of Science in Mathematics from Virginia Commonwealth University, where he studied from 2009 to 2013. He furthered his education by obtaining a Master of Science in Mathematics from Boise State University, completing his studies from 2015 to 2017. His academic background laid the foundation for his transition into data science in 2018. He specializes in machine learning applications, data analysis, and visualization, and is proficient in tools such as SAS, Python, SQL, and Excel.
Background
Sam Dworetzky transitioned from academia to a career in data science in 2018. This shift marked a significant change in his professional trajectory, allowing him to apply his mathematical knowledge to real-world data challenges. He has been based in Norfolk, Virginia, throughout his career at PRA Group, where he has developed a strong focus on leveraging data science techniques to enhance business performance.
Achievements
Throughout his career at PRA Group, Sam Dworetzky has engaged in various projects that involve data analysis and visualization. He has developed solutions that utilize data science techniques to improve business outcomes, particularly in optimizing customer interactions and business strategies. His commitment to learning new technologies and techniques reflects his dedication to continuous professional development in the field of data science.