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Ashley L. is a Data Scientist at TrueML since October 2018, with a background including a Data Analyst role at Earnin, where responsibilities encompassed end-to-end analytics for new products. Previous experience includes a Data Analytics Internship at Evernote, focusing on product usage modeling and A/B testing analysis, and a position as a Statistical Consultant at Epiodyne, specializing in EEG signal analysis for pain response detection. Additionally, Ashley served as a Global Data Insight & Analytics Intern at Ford Motor Company, where contributions included developing a multivariate regression model and automating forecasting workflows. Educational qualifications include a Master of Science in Data Science from The University of Texas at Austin (2021 - 2024), a Master of Science in Statistics from San Jose State University, and a Bachelor's Degree in Plan II Honors, Biology from The University of Texas at Austin.