Takashi Sakata, AI Solutions Department, Section 2, Digital and AI Technology Center, Technology Headquarters, Panasonic Holdings Co., Ltd.

What is a data scientist?

Panasonic Holdings Co., Ltd. Technology Headquarters Digital & AI Technology Center AI Solutions Department Section 2　Takashi Sakata(Ryuji Sakata)

■ Profile
After graduating from the Department of Aerospace Engineering, he joined Panasonic Corporation (then known as Panasonic) in 2012. He started working in data science with no prior experience and developed his skills on Kaggle, a global machine learning platform. He currently trains AI talent across the company and lectures at universities.

■What kind of work does a data scientist do?

A data scientist's job is to analyze data, extract meaningful information, and use it to help companies and organizations make decisions. They use programming and statistics to analyze a wide variety of data and find trends and patterns. They visualize the results and sometimes build predictive models, which can lead to business efficiency and improvement.
At Panasonic, I am responsible for analyzing a wide range of data related to products, business, and company management. For example, I analyze data from product manufacturing processes to identify the causes of defects and use this information to improve manufacturing processes and adjust equipment. However, the results of the analysis are not always accurate, so it is important to work closely with people on-site. I also utilize opinions on social media and customer data, taking real-life feedback into consideration, to help plan campaigns and other initiatives.

■Please tell us about your job satisfaction and future prospects.

The rewarding aspect of being a data scientist is gaining new insights from data and contributing to problem-solving. Seeing your analysis results actually being put to use in the field also boosts your motivation. Another attractive aspect is that you can grow and hone your skills by having an inquisitive mind about exploring and discovering data.
On the other hand, the work of a data scientist can be difficult. Data analysis does not guarantee results; it requires trial and error, like a treasure hunt. To obtain the desired results, it is necessary to determine the appropriate way to analyze the data at hand and to identify the appropriate analysis method.
In the future, I would like to broaden my knowledge of technology so that I can catch new technologies as they emerge, and aim to become a more professional.

■Message to students

Technology will continue to advance even further in the future. In this environment, it is necessary to absorb a lot of information, but I think it is best to look at it objectively and decide for yourself what interests you the most. Rather than only being exposed to new things and following trends, you should be exposed to both old and new and make your decision. We are required to constantly change so as not to be defeated by the current trends in the world, but you will grow the most when you are doing what you want to do.

Student Newspaper, October 1, 2023 Issue, Meiji University Graduate School 10st Year, Sakai Yaku