What is the career path for a data scientist? Useful Qualifications Also Explained

2024.04.11

  • Industry Information
データサイエンティストのキャリアパスとは?役立つ資格についても解説

Data scientist is one of the key occupations driving the era of big data. Demand for this profession, which requires a wide range of skills from data collection and analysis to the extraction of knowledge useful for business, is increasing in a variety of industries.

In this article, we will explain what kind of job title a data scientist is, and then detail the career path, job market trends, and qualifications useful for becoming a data scientist. We hope you will find this information useful for those who are interested in building a career in the data science field and for those who are seeking to improve their skills.

What is a data scientist?


データサイエンティストとは?

Let us begin by explaining what kind of job title a data scientist is, broken down by role and job description.

Role of a Data Scientist

Data scientists are professionals who use statistical analysis, machine learning, artificial intelligence (AI), data mining, and other technologies to create useful business value from vast amounts of data and contribute to business decision making and problem solving.

They not only analyze and visualize data, but also discover new knowledge by building machine learning algorithms and developing predictive models from the analysis results in order to create value from the data.

In this way, our main role is to facilitate data-driven decision making and help companies to more clearly determine the path to achieving their goals.

With the advent of the Big Data era, the amount of data available has increased dramatically, and maximizing its value has become a major challenge for companies. Against this backdrop, the demand for data scientists who have a deep understanding of data and can analyze and utilize it strategically is increasing every year.

In the past, data-related work was fragmented, but today, when strategic use of data is required, these tasks have been integrated into one specialized field, establishing the role of the data scientist.

Data Scientist Job Description

The job description of a data scientist varies from company to company, but in general, the data scientist is responsible for everything from understanding a company's business issues to formulating strategies, collecting, organizing, and pre-processing data, analyzing data, and reporting and making recommendations. Specifically, the following five main processes are involved.

  • Identification of corporate issues and strategy formulation
  • Establishment of data analysis environment
  • Data collection, organization, and preprocessing
  • Data analysis and hypothesis testing
  • Reporting and submission of output


Data to be collected comes in a variety of formats, including numerical values, graphs, and text, and these data are not provided in a uniform form. Data scientists are also responsible for creating a database environment in which these diverse data can be easily handled, converted, stored, and utilized.

Career paths that data scientists can pursue


データサイエンティストが目指せるキャリアパス

Data scientists can choose from a variety of career paths that utilize their data analysis skills and business knowledge. Typical career paths include the following positions

  • Project Manager
  • Senior Data Scientist
  • Growth Hacker
  • AI Engineer
  • IT Consultant
  • Management Consultant
  • Independent freelancer


From here, let's take a closer look at each of the above seven career paths one by one.

Project Manager

After building a career as a data scientist, you have the option of becoming a project manager. Project managers play an important role in directing and managing the overall project.

The main responsibilities of a project manager include

  • Developing project budgets and schedules
  • Organizing project teams
  • Responding to problems as they arise
  • Overall project management


The "data science skills" such as statistics and machine learning that you have developed as a data scientist and the "data engineering skills" such as building and operating a data analysis environment will be a great asset in your work as a project manager. They will be useful in various situations, such as overall project planning, risk management, and communication with team members.

However, in addition to experience as a data scientist, becoming a project manager also requires skills in overall project management and negotiation skills. A data scientist with these skills will have a smooth career progression to project manager.

Senior Data Scientist

A senior data scientist is a senior position in data analysis that builds on the experience and skills of a data scientist to address more complex issues. After gaining hands-on experience as a data scientist, you may advance your career to senior data scientist.

This position requires a high level of skill in all phases of data science, including data collection, analysis, modeling, interpretation, and visualization. In addition, as the leader of a team of data scientists within the company, you will be responsible for leading the team and managing projects.

Therefore, in addition to gaining practical experience as a data scientist, improving leadership and communication skills is also an essential element in pursuing this career path.

Growth Hacker

A growth hacker is a person who is involved in creating a system for the client company itself to grow by being involved in the development of products and services, in addition to website operation and improvement, web advertising operation, and data analysis, which are performed by web marketers.

The term "growth hacking" is a relatively new concept that was proposed in the United States in 2010 as a new role for web marketers. As a result, some people may still be unfamiliar with the term. However, this profession is expected to become increasingly important in the future in today's world, where efficient marketing methods are in high demand.

Since growth hackers are responsible for deriving the strategies needed for corporate growth from data analysis, they are closely related to data scientists and are one of the positions where their skills can be easily utilized.

AI Engineer

In addition to data analysis, those who want to be involved in more developmental work can consider a career path as an AI engineer.

AI engineers are professionals who develop new systems using artificial intelligence (AI) technology. AI engineers use advanced technologies such as machine learning and deep learning to build and manage a wide range of AI systems, including image and speech recognition, natural language processing, and future prediction.

The transition from data scientist to AI engineer is smooth, as there are many common skills, such as experience in handling large amounts of data and knowledge of algorithms and database design.

In addition, the knowledge of machine learning, deep learning, and database technologies such as SQL and NoSQL acquired as a data scientist can be directly utilized as an AI engineer, making it a good career advancement option.

IT Consultant

IT consultants use information technology to help client companies solve their business issues. They do not simply implement IT systems, but also contribute to corporate growth by gaining a deep understanding of the client company's issues and proposing optimal IT solutions.

Both data scientists and IT consultants share the same role of helping companies solve their issues by making full use of IT technology. Therefore, the skills and experience gained as a data scientist can be utilized in a variety of situations in the IT consulting profession.

In particular, data analysis skills are needed to solve clients' problems, and data scientists are good at complex data analysis using statistics and machine learning. These skills are very useful in the process of finding appropriate solutions for IT consultants.

Management Consultant

Management consultants provide professional advice and solutions in a wide range of areas such as business strategy, marketing, and business improvement in order to solve various problems faced by companies. Most companies have some kind of management issues, and management consultants provide specific solutions to these issues to support the growth of the client's business.

This position overlaps with IT consulting in some aspects, but while IT consultants specialize in problem solving using IT technology, management consultants approach the problem from a holistic management perspective, which means that their scope of work is broader.

In today's world, where decision-making based on data analysis is becoming increasingly important, the skills and experience gained as a data scientist can be put to great use in the work of a management consultant. For those who wish to take on large-scale management issues and lead corporate transformation, management consulting is an ideal career path.

Independent Freelance

After building a career as a data scientist, there is also the path of becoming an independent freelancer. With today's increasing demand for data analysis, the number of freelance data scientists is gradually increasing.

The greatest advantage of working as a freelancer is that you can freely choose which projects to work on because you do not belong to a specific organization. If you belong to a company, you cannot do only the work you want to do.

However, as a freelancer, you can focus on the industries you are interested in and pursue your expertise, or you can get involved in projects in a variety of industries to broaden your experience and skills.

However, to be successful as a freelancer, it is not enough to simply have strong technical skills. You must also have the sales skills to find clients and win projects, as well as project management skills. It is also important to continue to hone your data analysis skills to keep up with ever-changing technology in order to continue to receive high unit price projects.

Trends in the Data Scientist Job Market


データサイエンティストの求人市場の動向

The job market for data scientists has been expanding rapidly in recent years and continues to do so as of March 2024. According to a Yano Research Institute survey, the market for data analysis-related personnel (data scientists, analysis consultants, analysis architects, and project managers) is expected to reach 176,300 by 2025.

Reference: "Forecast of the Scale of Human Resources Related to Data Analysis in Japan," Yano Research Institute Ltd.

On the other hand, the supply of data scientists has not kept pace, and a serious shortage of human resources has become an issue. According to Hello Work job statistics, the effective ratio of job offers for data scientists in FY2023 is 2.77 times, which remains high.

Reference: Data Scientist - Occupation Details - job tag - Ministry of Health, Labor and Welfare


データサイエンティストになるのに役立つ資格

As a basic premise, there are no qualifications that you must obtain to become a data scientist. However, if you wish to advance your career as a data scientist, the following certifications will objectively prove that you have knowledge of data science and may give you an advantage when changing jobs.

  • Statistics certification
  • Data Analyst
  • Database Specialist Examination
  • Data Scientist Certification Examination
  • G certification and E certification


Let us explain one by one.

Statistics Certification Examination

The Statistics Certification Examination is a qualification test to evaluate statistical knowledge and applied skills conducted by the Japan Statistical Quality Assurance Promotion Association (JQAP).

This certification test is divided into 10 categories: the Statistics Certification Test (5 levels from Level 4 to Level 1), which certifies a wide range of knowledge from basic knowledge of statistics to advanced analytical methods, and the Statistical Surveys, Professional Statistical Surveys, and Basic, Advanced, and Expert in Data Science, which certify practical ability to apply statistics to business. The unique feature of this certification is that examinees can take the examination in any of the 10 categories according to their own objectives and purposes.

The Data Science Fundamentals, Development, and Expert examinations are more specialized in data science than the Statistics Examination, and we recommend taking this exam if you are aiming to become a data scientist.

It is recommended to start with the Data Science Fundamentals to understand the basic concepts of data science, and then aim to acquire more advanced knowledge and skills in the Developmental and Expert exams.

Reference: Japan Association for the Promotion of Statistical Quality Assurance

Data Analyst

The Data Analyst certification recognizes basic knowledge and skills in data analysis. It is conducted by the Institute for Practical Education, and is highly regarded as a "practical" qualification authorized by the Ministry of Education, Culture, Sports, Science and Technology.

To obtain this certification, you must complete a correspondence course called "Practical Multivariate Analysis Course" and then pass a certification examination for data analysts.

There are no special requirements for taking the exam, and the content is geared toward beginners, so this certification is also suitable for those who want to relearn the basics of data analysis. In the course, students can ask questions about points that are unclear and receive feedback by submitting assignments, allowing them to move on to the next stage with confidence while deepening their understanding.

Reference: Institute of Practical Education

Database Specialist Examination

The Database Specialist Examination is a national certification that certifies specialized knowledge and skills related to database design, construction, operation, and maintenance. It is one of the information processing engineer examinations administered by the Information-technology Promotion Agency, Japan (IPA), and is classified as an advanced examination category (Level 4).

Known for its high level of difficulty, this exam is highly recognized and trusted in the IT industry, and passing it proves that you have a high level of database-related expertise.

The pass rate for the past five years has been approximately 14~18%, and it is not easy to pass the exam, even for those with practical experience. However, with systematic study, it is possible to pass the exam. The official website provides past exam questions, so use these to study effectively.

In addition, only those who have obtained the Applied Information Technology Engineer certification are exempted from a part of the exam, which reduces the burden of learning.

Reference: Information-technology Promotion Agency, Japan (IPA)

Data Scientist Certification Examination

The Data Scientist Certificate is an examination designed to evaluate expertise in data science. In response to the increasing demand for personnel who can handle data, the Association of Data Scientists launched this new certification exam in 2021, and it is positioned as a private qualification.

By passing this certification exam, one can prove that they have the practical skills and knowledge of "data science," "data engineering," and "business skills" required of data scientists.

The certification test itself is divided into the following four levels, and currently only the Data Scientist Certification Test™ Literacy Level (abbreviated as DS Test® ★), which corresponds to the most basic "Apprentice Level," can be taken.

  • Assistant Data Scientist (Apprentice Level)
  • Associate Data Scientist (stand-alone level)
  • Full Data Scientist (Building Block Level)
  • Senior Data Scientist (industry representative level)


This certification test is intended for beginning data scientists, and there are no specific qualifications, so it is recommended as a first step for those who want to become a data scientist.

The official website provides detailed information on mock questions and the scope of the exam, as well as books and courses as learning support tools, so you can use these resources to prepare for the exam.

Reference: Japan Association of Data Scientists

G Certification and E Certification

Both the G-Certification and E-Certification are certification exams that help prove skills for deep learning applications and are sponsored by the Japan Deep Learning Association (JDLA).

While these two certification exams are similar in that they are designed to help people acquire AI/deep learning application literacy, the target audience, objectives, and scope of the exams are different.

First, the G-test is designed for businesspersons and generalists who want to acquire the skills to apply AI technology in business situations. It does not test the ability to implement deep learning itself, but rather aims to cultivate a basic understanding of AI technology, such as "what AI can and cannot do" and "where AI should be used," as well as the ability to apply AI to business.

The E certification, on the other hand, tests the ability to actually implement deep learning technology and develop systems, and is designed for engineers.

 G certificationE Qualification
Target AudienceFor business people and generalistsFor engineers
PurposeDetermine how to use deep learningImplement deep learning
Exam CoverageOverview of deep learning, application examples, and ethicsTheory of deep learning, model building, development environment, ethics
Difficultyeasier than E certificationMore difficult than G certification

Reference: Japan Deep Learning Association

Summary: If you want to build a career as a data scientist, acquire the necessary skills and qualifications.


This article details the career path of a data scientist, trends in the job market, and qualifications that are useful when changing careers. It is important for aspiring data scientists to acquire the necessary skills and qualifications to match their career plans.

At United World Inc., dedicated career advisors work closely with each individual to support their job search. After carefully listening to your detailed requirements and career plans, we will introduce you to the best job opportunities that suit you best, so please feel free to contact us if you want to conduct your job search efficiently.

Talk to United World about 
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