Over the last few years, the words “data scientist” have become increasingly common. But “data scientist” is still a new job type in Japan, and many people may not know what it entails.
In this article, we take a detailed look at what a data scientist does, what skills are required to become a data scientist, and what demand there is for data scientists on the job market.
If you want to find out more about the role of a data scientist - or if you are considering becoming a data scientist - this article may be of help to find out what are the skills required to become a Data Scientist.
What is a data scientist?
A data scientist analyzes data to find ways to overcome complex problems faced by a company.
The main tasks of a data scientists are as follows:
1. Identifying issues
A data scientist investigates problems and identifies specific issues facing a company.
2. Preparing data
In order to resolve these issues, the data scientist collects data, determines which data is important, and organizes this data.
3. Analyzing data
After organizing the data, the data scientist searches for information that will help resolve the company’s issues, and analyzes the data from various angles.
4. Recognizing patterns and visualization
The data scientist carries out “pattern recognition” to identify trends and rules in the data; the data scientist also “visualizes” the data in the form of graphs and diagrams to make it easier to understand.
5. Creating algorithms and data models to predict results
The data scientist uses machine learning to examine large amount of data, automating the analysis process and making predictions using data tools built in various programming languages such as Python, R, SAS, or SQL.
6. Creating reports
The data scientist summarizes the data, compiles status reports, and proposes improvements. The end-goal of the data scientist is to visualize the impact of issues facing the company, and provide stakeholders with discoveries, insight, and proposals.
In summary, a data scientist is an expert in analyzing data. For this reason, a data scientist is required to possess wide-ranging skills: these include technical IT skills, analysis skills, and the ability to use IT tools, as well as the ability to solve problems through logical thinking.
A data scientist must also be competent in mathematics and statistics, algorithms and machine learning, and communication.
What demand is there for data scientists, and what is the data market like in Japan?
Demand for data scientists is trending upward
Over the last few years, waves of digital transformation (DX) have surged through every industry, including IT, finance, apparel, logistics, medical, and government-related industries.
This trend is particularly marked at major corporations. Previously, companies primarily sought to improve work efficiency, lower costs, and increase profitability through internal digitalization; now, these same companies are utilizing digital technologies such as big data and AI not only to make improvements to their work processes but also to undertake full-scale transformations of entire business models.
For this reason, demand for data scientists is increasing across the board.
However, Japan lags other countries in digitalization. Indeed, Japan placed just 28th out of 64 countries in the World Digital Competitiveness Ranking 2021, published by the International Institute for Management Development. Singapore, China, and South Korea all ranked in the top 10—evidently, Japan is being left behind by its Asian neighbors.
A further issue is that there is no clear definition for “data scientist” in Japan, or for its corresponding business fields. This may result in mismatches between job seekers and companies which, in turn, may be contributing to the shortage of data scientists in the country.
Consequently, the supply of data scientists is presently unable to keep up with demand on the job market.
The current state of the data market in Japan
Viewed from a global perspective, the big data market has undergone huge growth. Today, data analysis is a prerequisite for the development of new business models and the establishment of management strategies.
There are growing data-related needs in Japan, too, occasioned by progress in digitalization across various industries, and by the popularization of smartphone payments and e-commerce markets.
IDC Japan forecasts an extremely high average growth rate in the Japanese data center service market of 12.5% between 2020 and 2025. Indeed, an increasing number of major corporations are collecting and analyzing big data to implement management improvements, while DX is also being promoted by the Ministry of the Economy.
The data market is therefore expected to expand, and demand for human resources capable of executing data analysis work is set to increase as well.
However, few small and medium-sized enterprises (SMEs) are fully embracing data analysis; the majority continue to rely on experience and intuition rather than data.
Is a data scientist an advantageous career choice?
Data scientists are required to possess diverse skillsets, including expertise in IT, high-level analytical skills (typically, this entails a master’s degree or PhD in STEM), outstanding communication skills, and a high degree of specialization. Personnel with expertise in IT cannot easily transfer across from other industries so, from a supply-demand perspective, it continues to be a seller’s market—being a data scientist therefore confers enormous advantages when it comes to the job market.
While the occupation of “data scientist” is still in its infancy, it is predicted that recruitment of data scientists will increase not only at major corporations but also at SMEs. However, there is a shortage of personnel in this field—particularly of employees who can be immediately effective—and key posts are yet to be filled at many companies. Simply being one of the first data scientists on the market is likely to place you in an advantageous position.
It is worth noting, however, that doubts exist about the future of the role of data scientists—some people claim that, as AI capabilities improve, so the role of data scientists will be eroded. There is indeed a high probability that simple tasks such as data collection and processing will be taken over by AI.
Nevertheless, data scientists are required to analyze data to propose solutions for various issues. This is complex work that comes with great responsibility, and AI is not a capable substitute. It is therefore hard to imagine that all data scientist jobs will disappear in the future.
Looking ahead to future career opportunities, since they are required to possess diverse skillsets, data scientists will also be able to pursue managerial and specialist occupations in various spheres of work, such as engineering or consultancy.
What are the skills required to become a Data Scientist?
As mentioned above, the role of data scientist requires diverse skillsets—strong IT, communication, and business skills are particularly important. Below, we look more closely at the exact skills required.
Technical IT skills
Data analysis requires the use of programming languages. A data scientist will therefore need to possess programming and other technical IT skills.
A data scientist will also need to be familiar with the programs used to manipulate big data, be able to identify important data and create graphs and other forms of data visualization, and be versed in analysis and statistical methods.
Concrete examples include the following:
- Programming languages such as Python, R, SAS, and SQL
- Data visualization tools such as Power BI, Tableau, and Domo
- Cloud computing services such as AWS, Azure, and Google Cloud Platform
The field of IT is constantly evolving. If you wish to become a data scientist, it is vital you continually learn new skills.
The work of a data scientist almost always requires communication with related parties.
Meetings are essential to identify issues, while presentation skills are also necessary to clearly communicate proposed improvements.
To be a data scientist, you must have knowledge of the industries you are working in; however, you do not necessarily have to know about a company’s specific industry before joining. The problem-solving mindset, business sense, and hard skills of a data scientist are highly versatile—they can be readily applied to different industries. In fact, the majority of data scientists only learn about specific industries after joining a company.
Logical thinking is also critical for solving problems. The more wide-ranging your business knowledge and the more ideas you have, the greater the likelihood you will be able to implement improvements in response to various issues. This will also elicit trust from those around you.
One method of acquiring knowledge is to study for qualifications. For example, The Japan Data Scientist Society runs a “Data Scientist Certification Test” which may be worth taking.
As DX progresses in Japan, so demand for data scientists is set to grow. At present, the supply of data scientists is unable to keep up with demand—and for this reason, it is a job for which there are many recruitment opportunities.
By utilizing the experience and skills you have acquired in other jobs, you may be able to find work as a data scientist, even if you have never worked as a data scientist before.
If you are looking for recruitment information related to the role of data scientist, or if you wish to receive career advice, please do not hesitate to contact Robert Half.