5 Strategies to Supercharge Your Earnings
The average computational engineering salary in the United States is around $81,500, according to salary.com. The highest-paid computational engineers regularly earn more than $100k.
Are you earning as much as you could?
With the construction industry accelerating toward greater digitalization and expanding use of computerized technologies, could you boost your salary by switching industries?
In this article, we discuss ways to improve your earnings as a computational engineer.
5 Strategies to Improve Your Computational Engineering Salary
You should have your salary under regular review. The events of the last year or so have improved the prospects for highly-skilled engineers in an uncertain world.
The switch to processes that are more reliant on emerging technology has been accelerated as people have been switched to working from home, and offices and workplaces have had to adapt to measures such as social distancing.
I recommend that you review your job and your earning potential at least annually, if not every six months. Especially in disciplines like computational engineering. If you believe you are being underpaid, here are five strategies to employ to get your earnings back to where they should be.
1. Ask for a Raise
The simplest way to boost your salary is to ask for a raise. Ask your boss for a meeting. Go prepared, with examples of the great work you do, and evidence of salaries paid for the skills and experience you possess in your industry.
Will your boss give you a raise? If you make a good case, there should be no reason why not. Remember, it costs money and time to hire and train a new employee should you leave.
2. Improve Your Knowledge
If your boss turns you down, the next step is to improve your knowledge. Learn new code languages and new instruments, and keep pace with technology developments.
Consider taking leadership courses and other training that improves both your hard and soft skills. Adding new skillsets makes you more valuable to the business, and that should allow to ask for a raise again.
3. Take on More Responsibility
Would you be prepared to take on more responsibility to earn more money? This is something else that you might consider doing and discussing with your boss.
4. Consider New Opportunities
Should you change jobs to get a raise? You may love your current employer, but do they love you? If they are not paying what you are worth, do they really value what you bring to the table? Studies show that staying with the same company too long is bad for your wealth. In an article published by Forbes titled ‘Employees who stay in companies longer than two years get paid 50% less’, research quoted includes:
- The average raise that an employee receives for leaving is between a 10% to 20% increase in salary
- Staying employed at the same company for over two years on average is going to make you earn less over your lifetime by about 50% or more (and assuming your career will last only 10 years)
New opportunities with a new company, perhaps with greater responsibility can improve your earnings now and in the future – providing you select the opportunity that enhances not only your salary, but also your experience and resume.
You might also consider changing location, which can have a massive effect on your salary. For example, the average computational engineering salary in Nashville, Tennessee is around $68,500. In Los Angeles, California, the average is around $20k higher.
5. Change Industry
As a computational engineer, your skills are highly transferrable – and not all industries pay the same. Taking a job in a different industry could be a very lucrative move for you.
Construction is in the top 10 of highest-paying sectors in the United States. As the sector continues its advance into technology-based solutions and operations, the demand for the skills that computational engineers possess is likely to increase.
Computational engineering is transformative to how the construction industry works. For example, putting designs into the digital world means they are easier to share, iterate, and work on in real time. This reduces mundane and repetitive work, increases the speed at which designs can be delivered, and ultimately allows the engineering team to focus on solving problems using insights without needing to manipulate data manually.