Data Scientist vs. AI Engineer: Which is Best Career?

technology

Oct 22

The data science market is expected to reach USD 178 billion by 2025, while artificial intelligence (AI) is predicted to grow at a compound annual growth rate of 13.7% and is anticipated to grow by USD 202.57 billion by 2026. Both fields have seen significant growth in the past few years, but which one is better? Which one should you choose? The truth is that both fields offer different job opportunities and appeal to different people. Not all data scientists are programmers, and not all artificial intelligence engineers are mathematicians. The difference between the two fields lies in their approach to solving problems. Data scientists use analytical tools to get their data and then make inferences from it; artificial intelligence engineers use algorithms and software to build systems that find patterns within data;

Making a career out of either data science or AI is a great choice, seeing as they are both market winners in the tech industry. The question now is: Which one is better? Data Science or Artificial Intelligence. First, let us understand both briefly.

Data Science:

The best career choice for any aspiring data scientist is a career in data science. Data science is a diverse field encompassing a wide range of skills and disciplines. It can be defined as the extraction and interpretation of information from data through the use of statistical and computational methods. Data scientists use a wide range of statistical techniques, including linear, nonlinear, and logistic regression and special-purpose software.

Artificial Intelligence:

AI engineers work hand in hand with data scientists to solve complex business problems. They analyze large amounts of data, build models based on that data, and then develop solutions to solve those problems. They combine art and science to create solutions that solve problems faster, more efficiently, and accurately. AI engineers build intelligent models in the form of software, hardware, or a combination of both. They design systems that leverage advanced machine learning techniques to improve business operations, support customers, or create new products and services.

Moving on further, let's have a quick comparison of the two popular job industries by analyzing the scope, demand, pay rate, and popularity of these careers.

Scope of Data Science vs. Artificial Intelligence:

The scope of data science is broad. It can cover anything from how companies hire data scientists to how businesses use data to improve their operations. A career in data science is a good choice for anyone who wants to work in technology but is not quite sure in what direction they want to go. The data scientist's primary responsibility is to collect, analyze, and act on information to make decisions based on accurate data.
The scope of artificial intelligence is rapidly expanding. As more and more industries and companies become dependent on this technology, the demand for AI specialists will continue to grow.

The demand for Data scientists and Artificial Intelligence engineer

Nobody can predict the future, but the one thing we can say is that data science, machine learning, and AI are changing the way companies do business and make decisions. And due to this data-driven era, companies need to hire people with expertise and knowledge of data science and AI. Analysts predict that the country will have more than 11 million job openings by 2026. In fact, since 2019, hiring in the data science and AI industry has increased by 46%.

Jobs and career in Data Science and Artificial Intelligence:

It’s a common misconception that Artificial Intelligence and Data Science are mutually exclusive careers. Not all job roles in Data Science and Artificial Intelligence are the same. However, there is often some overlap when it comes to the skillset required. The following table shows some career options in these exciting fields:

  
    Data Science
    Artificial Intelligence
  
    Data scientist
    Artificial intelligence engineer
  
    Data engineer
    Robotics scientist
  
    Data architect
    Machine learning engineer
  
    Statistician
    Big data engineer
  
    Data analyst
    Software engineer
  
    Machine learning engineer
    AI research scientist
  
    Business analyst
    Business Intelligence Developer

Salary of Data Scientist and AI Engineer:

The following table will show the salary range of the data science and AI engineers based on their experience level. This salary may vary from company to company.

  
    Experience Level
    Data Scientist (in INR)
    AI Engineer (in INR)
  

    Beginner (1-2 years)
    6-7 LPA
    5-7 LPA
  

    Mid-Senior (5-8 years)
    10-12 LPA
    8-10 LPA
  

    Expert (10-15 years)
    20+ LPA
    20+ LPA  
  

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