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Elaine Zanutto

Vice President Of Methods And Advanced Analytics at NAXION

Elaine Zanutto has extensive work experience in the field of statistics and data science. Elaine worked at NAXION from 2006, where they were the Vice President of Methods and Advanced Analytics. In this role, they led a team responsible for providing advanced statistical analyses and sampling methodology for market research consulting projects. Their expertise includes sample design, hierarchical Bayesian modeling, segmentation analysis, forecasting models, predictive modeling, simulator development, and structural equation modeling. Elaine also developed new statistical techniques as needed. Prior to NAXION, Elaine was an Assistant Professor of Statistics at the University of Pennsylvania, The Wharton School from 1998 to 2006. Their research interests during this time included consumer choice data analysis, causal analysis, sample survey design and analysis, imputation for survey nonresponse, and statistical estimation in the U.S. decennial census. In 2018, they became an Adjunct Professor of Statistics and Data Science at the University of Pennsylvania, Wharton School of Business.

Elaine Zanutto has a significant education background in the field of Statistics. Elaine completed their Ph.D. in Statistics at Harvard University from 1993 to 1998. Prior to that, they obtained a Master's Degree in Statistics from Carleton University, where they studied from 1991 to 1993. Their educational journey began with a Bachelor's Degree in Statistics from Carleton University, which they completed from 1987 to 1991.

In addition to their formal education, Elaine has obtained several certifications to further enhance their skills. Elaine received a Practical Machine Learning certification from Coursera Verified Certificates in October 2015. Elaine also completed courses in Programming for Everybody (Python) and R Programming, earning certifications from Coursera in August 2015. Furthermore, they hold edX Verified Certificates for Data Science and Machine Learning Essentials, as well as a certification for Scalable Machine Learning. The specific months and years for the edX certifications are not provided.

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