Stephanie Zhang is a highly competitive professional, specializing in business modeling, machine learning, growth hacking, and business tech-consulting. She has extensive expertise in supervised and unsupervised learning, deep learning, and time series. Stephanie has profound knowledge of Python, data analysis, modeling, visualization tools, NLP, and web scraping. In addition, she is skilled in using languages, software, and system tools such as SQL, Git, HDFS, Spark, and AWS.

Stephanie Zhang is a former data science fellow at Data Application Lab and a former operation specialist/analyst at Meritek Electronics Corporation. She also worked as a legislative intern at the Office of Council Member Gilbert Cedillo, City of Los Angeles, a data analysis intern at Intel Corporation, a management trainee at Huaxia Bank and Zurich Cantonal Bank, Hong Kong branch. Currently, she is a data scientist at Facebook.

Stephanie Zhang also has a successful history in hackathons, winning prizes at the Microsoft HoloHack, USC Supply Chain Hackathon, and IBM/DAL NonProfit Data Hackathon in 2017. She studied certificate in Neural Network and Deep Learning from Deeplearning.ai and graduated from the University of Southern California with a Master of Public Administration (MPA) in Public Policy, Public Administration, Urban Planning. She completed her Bachelor's degree in Management Information Systems from Beijing University of Post and Telecommunications.