Data scientists are high-tech professionals with the training and strong curiosity to make discoveries in the world of big data. Harvard Business Review dubbed data scientist as “the sexiest job of the 21st century.”
With more and more data becoming available, the role of those who turn it into something useful has become more in demand. To learn more about what a data scientist does, The Hanyang Journal spoke with Kim Okki, who uses her academic background to consult on the utilization framework of data and to develop products based on data service systems.
Q. What do you think is the reason for the recent attention on data science?
A. From the early 1980s, data base systems were based on SQL, a type of database language, and they were continually being developed by global IT companies, IBM and Oracle. Companies then collected data in the IT system and started to analyze the collected data from the late 1990s. Data analysis was primarily used for business interests. Then from the early 2000s, massive amount of data were analyzed and utilized, leading to the development of profit models in companies. After 2010, a new era of big data arrived where social data and sensor data became widespread. As a wide variety of data was utilized, data science took center stage in society.
Q. What drove you to choose your career path as a data scientist?
A. I actually wanted to be a foreign currency related analyst, not a data scientist when I went to the United States to study economics and finance. With a focus on statistics, I thought I could be an
analyst with a background in economics and finance, so I enrolled in a Master of Business Administration(MBA) program at the University of Akron, Ohio.
On January 1, 1995 when I finished the MBA course, Barings, a massive English bank and also the world’s second oldest, collapsed. At the same time, a staff member employed by Orange County of California caused great financial loss due to mismanagement of the county’s derivatives, leading to its bankruptcy. These incidents made me reconsider the risks of finance related businesses, and I decided to work in marketing areas instead. I entered Acxiom, a direct marketing company in Chicago as a data scientist.
Q. What do you consider to be the most important aspect of your work?
A. Theoretical principles of computer language, methodology for analyzing data, and hands-on experiences are all important. On top of that, the ability to communicate with others is also critical. Data scientists have to persuade many people in companies when presenting their hypothetical data, so the ability to clearly explain and persuade others in various fields about one’s ideas is necessary.
Q. Do you think your statistics background helped? Would you recommend anything to others interested in data science?
A. It is true that people who major in Statistics, Computer Science, Mathematics, and Industrial Engineering can have a smoother transition in becoming a data scientist. However, those with various undergraduate backgrounds like in majors of Business Management, Economics, Psychology, and Sociology can also be successful in data science.
Many domestic and international companies these days are looking for excellent candidates majoring in Business Management with knowledge of the humanities as well as being capable of dealing with statistical studies and tools for data visualization. I did not major in computers or science, so the most difficult part for me was learning about computer systems and programming language, which are fundamental knowledge in data science. However, I did not give up, and I gained hands-on experiences with my senior coworkers in my workplace. I also listened to lectures that I thought were necessary. In my experience, the most essential part of being successful is having an interest in the job itself, not the major.
Q. What would you say are things people need to do in order to work to their full capacity as a data scientist?
A. Educational programs to train data scientists have not been done well in Korea, but basic education is enough for data scientists. Gaining hands-on experiences at work is a shortcut because it takes at least five to eight years to reach the elementary levels of data science. I would recommend this work to those who are interested in computer programming. People with continued interests in analyzing data should consider this profession as well.
Q. What are your future plans as a data scientist?
A. I will keep trying to help Korean companies that are stuck in slow growth so that they can develop new technologies and services. These days, I am working hard to expand the data services, processing, and distribution industries in Korea, using my experience at Acxiom. I am especially active in Research and Development(R&D), and I am working as a lecturer too. It feels great to be in a position where I can apply my work experiences from overseas directly to help Korean industries grow. I will make persistent efforts to help Korean industries progress.