Yang Seagle Liu

Director Data Science at Veracyte

Yang Seagle Liu has extensive work experience in the field of data science and data engineering. They have held several senior positions and have worked for notable companies such as Veracyte, Inc., GenomeDx Biosciences Inc., and Google. At Veracyte, Inc., Yang served as an Associate Director, leading the Data Science & Data Engineering team. In this role, they developed a big data analytics database and led the development of various data delivery and visualization tools. Prior to joining Veracyte, Inc., Yang worked at GenomeDx Biosciences Inc. as a Senior Data Scientist and Data Engineering Manager. Their responsibilities included leading and supervising efforts in discovering actionable insights in high-dimensional genomic data, as well as designing and implementing a data engineering system. They also contributed to paper writing and provided data support to academic collaborations. Yang's previous experience also includes working as a Statistician at BC Center for Substance Use, where they conducted statistical analysis and used machine learning methods to convert messy survey data into health policy insights. They also automated routine statistical analysis and reports. Additionally, Yang gained experience as a Data Scientist/Quantitative Analyst Intern at Google, where they evaluated mathematical assumptions and ran simulations to assess the impacts of sampling variability on machine learning models. Prior to that, they worked as a Statistical Consultant at STCS, UBC. Throughout their career, Yang has demonstrated expertise in machine learning, bioinformatics, data engineering, and statistical analysis.

Yang Seagle Liu completed a Bachelor of Science (B.Sc.) in Mathematical Statistics and Probability at Nankai University from 2006 to 2010. Following this, Liu pursued a Master of Science (M.Sc.) in Statistics at The University of British Columbia from 2010 to 2012. Finally, Liu obtained a Doctor of Philosophy (PhD) in Statistics from The University of British Columbia, where they studied from 2012 to 2017.

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Timeline

  • Director Data Science

    March 1, 2024 - present

  • Associate Director, Data Science & Data Engineering

    March, 2022

  • Senior Data Scientist And Data Engineering Manager

    March, 2021