What will happen to a young data scientist who just graduated from school after entering an industry? What is the difference between experiments and applications to solve real world problems using data science? In this talk, I will share my journey from a new machine learning and data mining graduated student to a senior data engineer (Or sometimes, the data scientist). How to detect and define problems? How to understand the domain knowledge and combine it into data models? How to apply data science to solve them? How to ensure the data correctness during ETL process? How to evaluate the performance? Is there any better solution? Etc. Becoming a data science unicorn for one single person is difficult. How about a group of talents? To build a successful data product, cooperation with people from different functions is needed. In the end, I will share the experience working with different departments and how we achieve better result by leveraging knowledge from every domain.
Stephanie Chou received the B.S degree and M.S. degree in computer science from the National Taiwan University of Science and Technology in 2011 and 2013. Since then, she has been a data engineer at Oath APAC Data Team, working on business intelligence and customer relationship management system. She currently focuses on recommendation and targeting system.