Michael Silger
About Michael Silger
Michael Silger is a Lead Data Scientist with extensive experience in demand planning and statistical analysis. He has developed innovative forecasting solutions and led data science initiatives across multiple organizations, including Nestlé and Poly.
Work at Poly
Michael Silger has been serving as the Lead Data Scientist at Poly since 2020. In this role, he has focused on enhancing data-driven decision-making processes. He built models to predict claim rates, which improved the accuracy of quarter-end financial projections. Additionally, he initiated a data science team within the IT department, aimed at providing business-facing services. His contributions have played a significant role in streamlining operations and improving financial reporting.
Previous Experience at Nestlé
Before joining Poly, Michael Silger worked at Nestlé as the Lead Data Scientist from 2016 to 2019 in Kobe, Hyogo, Japan. During his tenure, he developed a hierarchical time series forecasting solution in AZURE for demand planning. Prior to this position, he served as a Senior Demand Planning Statistician at Nestlé Purina North America from 2013 to 2016 in St. Louis, Missouri. His experience at Nestlé involved significant contributions to demand forecasting and statistical analysis.
Data Science Consulting Experience
Michael Silger worked as a Data Science Consultant from 2019 to 2020 in the Colorado Springs area. This role allowed him to apply his expertise in data science to various projects and clients, further enhancing his skills in statistical analysis and demand forecasting. His consulting experience contributed to his comprehensive understanding of data-driven methodologies.
Education and Expertise
Michael Silger earned a Master of Arts in Statistics from the University of Missouri-Columbia. He studied there from 2011 to 2013, building a strong foundation in statistical methods and data analysis. His educational background is complemented by an earlier period of study at the same university from 2007 to 2013, where he further developed his expertise in statistics.
Achievements in Financial Reporting
Throughout his career, Michael Silger has automated month and quarter close activities, which expedited financial reporting processes. His initiatives in this area have contributed to more efficient operations within the organizations he has worked for, demonstrating his ability to leverage data science for practical business applications.