Yibo Ma graduated with a Master’s degree in Communication Data Science at USC and is a data scientist at Warner Bros. Entertainment. His undergraduate major was advertising. Throughout years at USC, he became a data enthusiast and gained technical skills such as Python, R, SQL, Tableau, SPSS and Google Analytics. He suggested that beginners should start with something simple and should have a life-long learning attitude just like data science experts do.
- What are your undergraduate and graduate majors?
I recently graduated with a M.Sc. in Communication Data Science at USC. My undergraduate major was advertising. I am currently working as a data scientist at Warner Bros.
- What was your turning point (event, person, or work) that motivated you to study data science?
Probably since I did some marketing research for a marketing research class when I was an undergraduate. I found doing data analysis was interesting and meaningful, not only to me but also to decision-making. Then I took more courses about statistics and methodology and decided to apply for data analytics programs in the US. Being admitted by USC and having the chance to learn from those awesome professors and outstanding peers is the luckiest experience I have.
- Have you worked in the field of data science (either a work or a research experience)?
Yes. Both work and research.
- Looking back to the beginning of your journey, do you have any advice for students or beginners who want to learn more about data science?
Stay curious and eager about the knowledge that you don’t have. Being a qualified data science practitioner requires a life-long learning attitude. From my personal experience, I would recommend students who don’t have a computer science background start from something simple and develop their interests in data science first. For beginners, you don’t have to stride along the learning path and then get intimidated and overwhelmed by too much unknown. Building confidence is really important.
- How will you apply your skills to solve real-world problems? Why do you care about solving this problem?
Specifically, I used SQL to do data wrangling and python/r for data preprocessing and ad-hoc analyses. Some of the analyses involve statistical inference and A/B testing and some involve machine learning modeling. Our stakeholders in the company are interested in varied topics, like user engagement, browsing behaviors, and advertisement performance. Communicating the outputs of analyses to the stakeholders is really important and often implies data visualizations and end-to-end products for better explainability.
Why do we care about solving that problem? Because the outputs help the company drive more profits or save unnecessary expenses by investing in the right products. They also draw a clear picture of user behaviors and what content users like or dislike. This proves the value of data science to our stakeholders inside the company.
- Why do more people need to study data science?
Tons of data are generated on a daily basis and waiting to be analyzed. Without a strict and reliable analysis, data is just data and it won’t be converted into insights. Our society needs data science experts to produce values from various raw and unorganized data. Besides, from the perspective of finding a job, there are many needs for data science professionals among all kinds of companies and organizations. Learning data science can make you the person who helps them quantify the outputs of their work and improve their business processes.