Yang Cong, PhD

Yang Cong, PhD has a diverse work experience in data science and analytics. Currently, they serve as the Director of Analytics at PureCycle Technologies. Prior to this, they worked as a Data Science Manager at LyondellBasell and as a Vice President of Data Science at Gryphon Oil & Gas.

Before joining these companies, Yang worked as a Principal Data Scientist at Wood Mackenzie, where they utilized advanced data analytics to provide insights to clients and internal research and consulting teams.

Prior to that, they held the position of Senior Data Scientist at Sanchez Oil & Gas Corporation, where they brought insights and actionable strategies to the higher management level through data analysis.

Yang also worked as a Data Scientist at Schlumberger, where they conducted various projects related to tool reliability analysis, down hole environment analysis, and operation planning.

Besides their professional experiences, Yang also founded DataScienceMom, where they built analytics projects and promoted data analytics through sharing knowledge.

Earlier in their career, Yang worked as a Postdoctoral Associate at The Methodist Hospital System, where they applied their analytical skills to clinical projects. Yang also worked as a Research Assistant at The University of Hong Kong, where they built statistical models and designed algorithms for predictive and decision-making topics.

Yang's work experience also includes being a Research Fellow at Houston Methodist, where they extracted and integrated data and delivered analysis reports for clients in different fields.

Yang Cong, PhD, has an extensive education history that includes multiple degrees and certifications. In 2003, they obtained a Bachelor of Science (B.S.) degree in Information and Computing Science from Dalian University of Technology. Yang then went on to complete a Doctor of Philosophy (Ph.D.) in Computational and Applied Mathematics from The University of Hong Kong in 2012.

In addition to their formal degrees, Yang has pursued various executive education programs and online courses to enhance their skills and knowledge. From 2014 to 2015, they completed the Data Science Specialization from The Johns Hopkins University through Coursera. In 2015, they participated in the MIT Professional Education's online program "Tackling the Challenges of Big Data" from the Massachusetts Institute of Technology. Moreover, Yang completed the Machine Learning Specialization from the University of Washington in 2016.

Yang's commitment to continuous learning is evident through their participation in various certifications and programs. Yang obtained a Certification in "Intro to Hadoop and MapReduce" from Udacity in 2014. In 2017, they completed the Deep Learning Nanodegree from Udacity, and they also received the edX Verified Certificate for Introduction to Microsoft Azure. Yang further expanded their expertise by obtaining certifications in areas such as cloud computing, Apache Spark, R programming, and machine learning through Coursera and edX.

Yang Cong's pursuit of knowledge extends beyond their background in mathematics and data science. Yang has also engaged in executive education programs offered by prestigious institutions. In 2019, they enrolled in the Leadership and Management program by Harvard Business School Online. Yang continued their education at Harvard with the Credential of Readiness (CORe) program in 2019-2020 and completed a program in "Competing in the Age of AI" from Harvard Business School Executive Education in 2022. Furthermore, Yang enhanced their negotiation and leadership skills through the Harvard Law School Executive Education program in 2021 and explored supply chain management through programs at The Wharton School in 2020 and 2021.

Yang Cong's dedication to continuous learning is further demonstrated by the additional certifications they have obtained. Yang completed certifications in areas such as plastics recycling, supply chain management, shale hydraulic fracturing, and competitive advantage.

Overall, Yang Cong, PhD, has a diverse education background, encompassing formal degrees, online courses, executive education programs, and various certifications, all contributing to their expertise in computational and applied mathematics, data science, machine learning, and leadership.