Naoko Tomioka

Naoko Tomioka has a strong background in data analysis and research. Naoko currently works as a Data Scientist at Clio - Cloud-Based Legal Technology, where they have been employed since October 2019. Prior to that, they worked at Benevity for three years, starting as an Operations Analyst and later transitioning to the role of Insight Analyst. Before joining Benevity, they spent four years at iPerceptions, working as a Data Scientist and Linguist. Naoko also has experience in localization and production coordination, having held positions at Softitler/Deluxe Digital Studio and Softitler. Naoko completed their post-doctoral research at UQAM and served as an Instructor at Concordia University for a brief period. Overall, Naoko's work experience demonstrates their expertise in data analysis and research, as well as their ability to adapt to different roles and industries.

Naoko Tomioka completed their Bachelor of Arts with Honors (BAH) at Queen's University from 1997 to 2000, with a specialized field concentration in Linguistics, Spanish, and Psychology. Naoko then pursued their Ph.D. in Linguistics at McGill University from 2000 to 2006. In 2001, Naoko attended the LOT (the Netherlands National Graduate School of Linguistics) Summer School to further their knowledge in Linguistics. Naoko also attended the Vivian Smith Advanced Studies Institute of the International Neuropsychological Society's Summer Institute in 2002, focusing on Neuropsychology. In 2004, they briefly studied at Kent State University's School of Speech Pathology and Audiology. Naoko later obtained a Post Graduate Diploma in Management with a Health Care Concentration from McGill University in 2012 and 2013. Additionally, they have obtained various certifications such as "Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization," "Structuring Machine Learning Projects," "Neural Networks and Deep Learning by deeplearning.ai," "Regression Models," "Statistical Inference," and three edX Honor Code Certificates related to Data Analysis, Data Science and Machine Learning, and Machine Learning for Data Science and Analytics.