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Career in Data Science for Mechanical Engineers

Updated on 01 February, 2024

Gauri Agrawal

Gauri Agrawal

Sr. Content Writer

In today’s rapidly evolving world, every industry has become data-driven. We create humongous amounts of data every day with heavy usage of the internet around the world. This ever-growing volume of data has resulted in the increased demand for data scientists in businesses. 

If you wish to make a Career in Data Science for Mechanical engineering then you should be knowing the aspects associated to it. Data Science is a diverse field that uses analytical frameworks and calculations to extract valuable insights from different data types. To define it simply, data science combines various areas, such as informatics, statistics, and data analysis, that help understand and analyze data. 

In this article, you’ll get a brief idea of the career options data science holds for mechanical engineers. 

As one of the most profitable domains of today’s world, data science offers various career opportunities for individuals from different backgrounds. One of the most popular backgrounds in mechanical engineering overlaps with data science in several ways. As a result of technological advancements, nowadays, mechanical devices are designed using efficient systems and techniques to improve their functioning. 

If we talk about today’s scenario, there are limited tools available for mechanical engineers. These tools are mainly used for processes including hardware design and machine control. Although there is reliable software such as CATIA, ANSYS, MATLAB, and Abaqus, they aren’t easy to use. Therefore, any small error in the project can create a massive disaster for engineers and managers. 

This is where the role of data science comes in. Data scientists help build software to update with new data information, making it easier to measure the performance of several factors such as mechanical equipment, environmental conditions, etc.

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How is Data Science and Mechanical Engineering related?

Being one of the most profitable domains of today’s world, data science offers a wide range of career opportunities for individuals from different backgrounds. One of the most popular backgrounds in mechanical engineering that overlaps with data science in several ways. 

As a result of technological advancements, nowadays various mechanical devices are designed using efficient systems and techniques to improve their functioning. 

If we talk about today’s scenario, there are limited tools available for mechanical engineers. These tools are mostly used for processes including hardware design, and machine control. Although there is reliable software such as CATIA, ANSYS, MATLAB and Abaqus, they aren’t easy to use. Therefore, any small error in the project can create a huge disaster for engineers and managers. 

This is where the role of data science comes in. Data scientists help in building software to update with new data information that further makes it easier to measure the performance of several factors such as mechanical equipment, environmental conditions, etc.

Applications of Data Science in Mechanical Engineering

Various applications of data science in mechanical engineering are as follows- 

  1. Biomechanical Applications
  2. Solid Mechanics Applications
  3. Robotic Applications
  4. Control Engineering Applications
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What advantages do Mechanical Engineers get from Data Science?

There are several advantages that Mechanical Engineers can get from Data Science, one of the most significant advantages being the ability to reduce gaps in massive data sets within an organization. 

Learning data science gives mechanical engineers an edge over their competitors as they can develop their skills in a short period and apply for high-paying jobs. Besides this, studying data science allows mechanical engineers to learn different programming languages, making it easier for them to create scalable and efficient solutions.

The transition from mechanical engineering to data science

Before transitioning from mechanical engineering to data science, there are some skills that mechanical engineers must have. These skills include- 

1. Math and Statistics

From an engineering background, mechanical engineers are already well versed in mathematics. As a part of applied mathematics, statistics are a significant part of their study. Therefore switching to data science gets easier for mechanical engineers. 

2. Domain Knowledge

Domain Knowledge is one of the essential skills a data scientist must possess. The three main aspects of these skills include- 

  1. a) Recognizing the source of the problem,
  2. b) Figuring out the mechanisms of data collection,
  3. c) A detailed understanding of business operations

3. Programming

Knowledge of programming tools such as Java, SQL, Scala, R, and Python is a must-have skill for data scientists.

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Where do mechanical engineers fit in data science?

Data science has room for several job roles due to its wide and diverse application and job prospects. Hence it becomes mandatory to get yourself acquainted with the career opportunities before switching to the data science industry. Below are some of the top job roles in data science:

1. Data Analyst

The role of a data analyst is to collect, store, and evaluate large sets of data. Along with programming and mathematical skills, data analysts must possess data handling and data visualization.  

2. Data Scientists

Data Scientists are one of the most highly-paid professionals. They partially fulfil the role of mathematicians, computer scientists and trend spotters by acting as a link to the IT and business sectors.  

3. Data Engineer

A data engineer collects, maintains and converts data into meaningful information that can be utilized by data scientists and business analysts. They used programming tools such as Scala, Apache, Java and Hadoop. 

4. Business Analysts

Business Analysts find out how data can be used to gain business insights that result in growth.

Given below is the average annual salary for individual job profiles in data science.

Job ProfileAverage Annual Salary (in USD)
Data Analyst$65,795
Data Scientists$101,736
Data Engineer$115,094
Business Analysts$82,624

Source File: https://www.indeed.com/career/data-scientist/salaries

Conclusion

Learning data science can be both challenging and valuable for mechanical engineers. Due to the rising demand for data scientists in every industry, there are endless opportunities that data science holds for individuals from mechanical engineering backgrounds.  

This article covers every aspect of the transition from mechanical engineering to data science. We hope it works in favor of the individuals looking forward to exploring careers in data science.

Frequently Asked Questions

Can a Mechanical engineer become a data scientist?

Mechanical engineers have a strong background in physics and mathematics, which helps them to enhance their skills and learn technical aspects of data science.

What skills are required for mechanical engineers to transform their career into Data Science?

Before transitioning from mechanical engineering to data science, there are some skills that mechanical engineers require, which are: Programming, Domain Knowledge, Math, and Statistics.

Is data science a promising career for mechanical engineers?

Data science is one of the most profitable domains of today’s world, which offers a wide range of career opportunities for individuals from different backgrounds. One of the most popular backgrounds in mechanical engineering overlaps with data science in several ways. Hence data science is a promising career for mechanical engineers.

Who earns more, mechanical engineers or data scientists?

According to payscale, data scientists earn more than mechanical engineers; the average annual salary of data engineers is $115,094, wherein mechanical engineers earn around $83,160 in the US.

Gauri Agrawal

Sr. Content Writer

Gauri Agrawal is a passionate, professional and proactive content marketer who wants to grow in the field of content creation. She carries a rich experience of working in the Digital News sector with renowned names like Times Now Digital, and News X as a Copy Editor.

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