Qingxia Yu (Quency)

Quency Yu has a diverse work experience in the field of data science and machine learning. Qingxia (Quency) is currently working as an Applied Scientist at Fetch Rewards since April 2022. Prior to that, they were a Machine Learning Engineer at the same company from June 2021 to April 2022.

Before joining Fetch Rewards, Quency worked as a Data Scientist at FINRA from March 2020 to May 2021. In this role, they developed a machine learning autoencoder model to detect unusual market trading activities and built regulation strategies using Python and Databrick. Qingxia (Quency) also accelerated the model using Pytorch GPU clusters and created a web-scraping application to collect external financial reports.

Quency's previous experience includes working as a Research Assistant at the University of Maryland from August 2019 to December 2019. Additionally, they worked as a Data Engineer at iSolvers, Inc. from May 2019 to December 2019.

Overall, Quency Yu has demonstrated expertise in machine learning, data engineering, and research.

Qingxia (Quency) Yu completed their Bachelor of Arts (B.A.) in Business Administration and Management, General at the University of California, Irvine - The Paul Merage School of Business from 2012 to 2015. In 2018, they pursued a Master of Science (MS) in Data Science at the University of Maryland - Robert H. Smith School of Business, which they completed in 2019.

In addition to their formal education, Qingxia has obtained several certifications. In 2017, they completed the "Machine Learning Foundations: A Case Study Approach" course from Coursera. In 2020, they acquired the "Amazon Web Services Cloud Practitioner" certification from Amazon Web Services (AWS). Qingxia also has a certificate from SAS in Library but the specific details like when and where they obtained it are not provided. Similarly, they have completed a course in "Interactive Programming in Python," and another in "Linear Algebra" through edX, but the dates and institutions for these certifications are not specified in the provided information.