Thursday, April 18, 2024

Data Scientist vs. Machine Learning Engineer- The Better career option

The importance of both these positions of data scientists and machine learning engineers has grown significantly in the 21st century. Now that every industry is going through a technological evolution, the requirement for a machine learning engineer naturally increases. This doesn’t mean that the value of a data scientist is reduced in the process. In fact, instead of looking at these two roles as competitors, it is better to look at them as the collaborators they are.

From small startups to huge companies, everyone needs a data scientist to analyze all the company and customer data for the organization and provide data-driven insights to the management team. But when it comes to transforming data into real solutions, it becomes the responsibility of a machine learning engineer to create the ideal innovative solutions. This is why it is encouraged for every tech professional to do the machine learning course (free), as it makes the collaboration process very smooth.

Difference between Data Scientist and Machine Learning Engineer

Data scientists, as well as machine learning engineers, all these AI-based job roles are gaining popularity in the new era of technology. Many industries are already encouraging their data scientist and IT professionals to get trained in machine learning. If you already understand data and engineering, becoming a machine learning engineer will be easy.

A Data Scientist is someone who tries to make sense of the data that has been collected and then uses different software for analysis. On the other hand, a Machine Learning Engineer does not need any data as it uses algorithms to produce results.

As data scientist and machine learning engineer are two different roles, there are some apparent differences between the two. There is a difference in skillset, tools used, responsibilities, and salaries these positions offer.

Let’s discuss these differences below:

Differences in skill set:

Data scientists and machine learning engineers both have some skills that overlap with each other. For example, skills such as having an understanding of some common programming languages and being able to do the statistical analysis are necessary skills for both jobs.

But let’s look at the skills specific to a particular job.

Machine Learning Engineer skills:

The skills you need to become a competent machine learning engineer are as follows:

Language, Audio, and Video Processing

It is common for a machine learning engineer to work with text, audio, or video as a part of natural language processing. So that includes having reasonable control over various libraries and techniques for processing.


Many of the mathematics you learned during your computer science degree will be useful in your machine learning job. You will be required to create algorithms for systems, which means you must know how to use various mathematical functions and theories.

Software Development

No matter the type of IT engineer you are, you must be good at software development. Creating various algorithms and AI programs is similar to creating web applications.

Data Scientist skill set:

Becoming a data scientist means you need to have the following skills:

Critical Thinking

Figuring out problems by looking at numbers and raw data requires extreme critical thinking. Once you have the issues, you must find the appropriate solutions.

Communication Skills

A lot of the time, data scientists have to communicate with various teams with little to no experience in the domain of the problem and how to find the solutions effectively. They also have to be able to convince the management and the stakeholders to go through with certain difficult decisions.

Problem Solving

These professionals are responsible for identifying various business problems and finding the right solution. Working with machine learning engineers, the data scientists also must keep the solutions ML-oriented.

Differences in responsibilities

A significant difference in the skillset also means a tremendous difference in the roles and responsibilities of the professionals.

Let’s look at the typical tasks these two professionals are responsible for during their daily work hours:

Responsibilities of a Machine Learning professional

  • Collaborate with data scientists and study their data to create the best prototypes for business solutions.
  • Create artificial intelligence and machine learning systems to work with.
  • Use various ML tools and algorithms to create the best solutions.
  • Understand the requirements of the client and the business and develop the most innovative applications.
  • Regularly run tests in machine learning and keep on experimenting with the systems.

Responsibilities of a Data Scientist

  • Understand the machine learning techniques and provide solutions that fit the requirements.
  • Maintain a good relationship with the customer and provide them with the proper guidance to advance their business.
  • Verify all the data being analyzed and then process and cleanse that data to get results.
  • Research the market thoroughly for every client and every new industry.
  • Identify the strengths and weaknesses of the company using the data collected.

Differences in salaries

According to PayScale, a career in data science in India will earn you a salary of ₹892,595 per year. This salary package will also include non-cash benefits such as 401K, commute assistance, and various health insurances.

Similarly, a career in machine learning engineering in India will earn you a salary of ₹1,333,333 per year with non-cash benefits such as 401K, health insurance, and a flexible work schedule.

Which is the better career option?

This can depend on the job you want in the long run. If you want a career where you have an opportunity to be creative and do more research, you should choose Data Scientist. However, if research is not your strength and you would like to learn something new every day, Machine Learning Engineer could be the better choice for you.

Depending on the way you are looking at these two roles your conclusion as to which career option is right for you might differ. On one hand, machine learning engineers get a better salary with similar additional benefits, check for free online courses but on the other hand, the demand for data scientists in the job market is higher.

This has a good chance of changing in the future though as technology will be adapted in more industries, the requirement for machine learning engineers will increase. So if you are on the way to becoming a data scientist and looking at the future outlook you might want to start thinking about a career transformation from now on.

Lindsey Ertz
Lindsey Ertz
Lindsey, a curious soul from NY, is a technical, business writer, and journalist. Her passion lies in crafting well-researched, data-driven content that delivers authentic information to global audiences, fostering curiosity and inspiration.

Related Articles