On the surface, mechanical engineering and data science couldn’t be more different, right? As a mechanical engineer, you build, test, and deploy machines—think internal combustion engines, medical devices, and air conditioners.
Data scientists, on the other hand, don’t create anything physical. Instead, they build, test, and design far more abstract things— think data algorithms and machine learning models.
That said, it’s quite possible to become a data scientist with a mechanical engineering background. Find out how below.
Similarities Between Mechanical Engineers and Data Scientists
Mechanical engineers and data scientists are analytical by nature. Both come up with an idea—perhaps for a new machine or a way to interpret data—and then turn that idea into a reality. Both work as part of a team. Both require math skills. Both require coding knowledge, although data scientists need much more!
You can now see where these two professions overlap, making the career jump from mechanical engineer to data scientist not such a crazy concept after all!
In recent years, data science has started to creep into mechanical engineering. Take machine learning and artificial intelligence, for example. You probably already use these technologies in your day-to-day job, just like data scientists have been doing for years. According to Carnegie Mellon University’s mechanical engineering department, machine learning and AI help engineers:
- Create concepts for cars and aircraft with design DNA
- Detect problems during 3D printing
- Design virtual reality engineering simulations
- Turn drawings into interactive simulations
- Make self-driving cars smarter
- Map air pollution
If you know about machine learning and AI, you could easily transition to data science with the right training and experience in a data-specific role.
How a Mechanical Engineer Can Become a Data Scientist
While mechanical engineers, especially those who use machine learning and AI in their jobs, share some similarities with data scientists, there’s still a lot to learn. That’s because data science involves far more than just coding, math, and an analytical mind.
The foundation of data science is the ability to exploit data to serve a particular purpose—skills you probably lack. You might use a machine learning model when designing and testing machines, but it’s unlikely you interpret and manipulate data, at least not like a data scientist. So, if you want to move from mechanical engineering to data science, be prepared for a steep learning curve! However, with hands-on training and lots of perseverance, there’s no reason you can’t make this switch.
Any good data science program will teach you the skills to land a job in the exciting world of data. Those skills include data wrangling, data visualization, predictive modeling, statistical modeling, and many more. Some of these concepts might be completely alien if you have a mechanical engineering background. But remember, you weren’t born a mechanical engineer. You had to learn the skills required for your job. So, making the transition simply means acquiring some new skills.
This shouldn’t be a problem. The best data science programs allow you to work alongside world-class instructors with real-world data sets. Over time, you’ll develop a data science portfolio that showcases your work and increases your chances of landing paid work. You can also gain practical experience through paid or unpaid internships with companies offering them in data science departments.
If you have little actual data science experience, there might be a few barriers to getting a place in a program. The best ones require a master’s degree or Ph.D.—or, at the very least, a bachelor’s in a data-related subject. You’ll likely have to complete a coding test to showcase your programming skills. But if you already have the right qualifications and experience—perhaps you code on the side or program at an advanced level in your current role—you can enroll in a program whenever you like and kick-start your new career.
Why Would a Mechanical Engineer Become a Data Scientist?
Mechanical engineering and data science are both high-paid and in-demand jobs. However, the average salary for a data scientist ($124,518) is around $35,000 higher than a mechanical engineer’s ($89,016). That’s one reason so many people want to enter the world of data science.
But it’s not all about the money. One of the best aspects of being a data scientist is the ability to solve real-world problems with data. Sure, mechanical engineering is all about problem-solving, but data scientists use even more analytical capabilities in their jobs than engineers. Thanks to their interpretation of data, scientists can identify ways to save a business from going under, uncover business intelligence that changes lives, and even make a huge social impact using data to figure out how nonprofits can best divert their resources, for example.
Is it possible to make the switch from a mechanical engineer to a data scientist? Most definitely. While these roles are fundamentally different, mechanical engineering and data science share some similarities, so this career jump is more than doable. If you already have intermediate coding skills and the right qualifications, you can enroll in a data science program as soon as today. You’ll learn a heap of new concepts that you might not be familiar with but, over time, you’ll develop the talents you need to land a high-paying job as a data scientist.
What Are You Waiting For?
Ready to kick-start your data science career? There’s never been a better time than now. The Data Incubator has you covered with its data science boot camps and programs, helping you master the skills for your dream job.
You can learn more about our programs here:
- Data Science Bootcamp: This provides you with an immersive, hands-on experience. It helps you master in-demand skills to start your career in data science.
- Data Engineering Bootcamp: This program teaches you the skills to build data infrastructures, design better models and effortlessly maintain data.
We’re always here to guide you through your journey in data science. If you have any questions about the application process, consider contacting our admissions team.