By Fatima Haroon
December 10, 2022
Data science is full of untapped potential and opportunities. It isn’t uncommon for professionals from academia to transition to the data science industry. So, if you are an individual working as a lecturer or researcher in quantitative fields such as physics and engineering or data science degree programs and are interested in data science, you need professional guidance.
If you have questions like:
“What about my many years spent in academia?
What about all the courses and classes I took and taught in college and high school?
Are they going to be completely wasted if I leave academia?
What is it for me in the industry?
What does it look like to leave academia and work in the industry for private companies?
Who are the people I will be working with within the industry?
Are they intelligent people? Am I going to lose my credibility by leaving academia?
Have people done that in the past? What happened to those people?
Am I going to regret my decision later on? Can I go back to academia if I don't like working in the industry in the Data Science space?”
We are here to address them. So, let’s get started.
We know that staying in your ‘research’ bubble is what you might prefer. You may be cautious about stepping into this new world. But this doesn’t mean that there are no opportunities for you here. Instead, data science is an in-demand skill with a vast talent gap.
You can be the perfect candidate to fill this gap with your skills. If you are thinking about transitioning into this field, this means that you are interested and you want to. Not taking this bold step right now will result in future “what ifs” and potentially harm your successful career.
If you love data science and think you will enjoy working as a data scientist, go for it. There’s nothing strange about pursuing your dreams. Many people have successfully transitioned to this field, and you can do it too.
If you do it rightly, you will never look back or regret your decision. However, if you ever want to switch back to academia, you can without it being frowned upon. So, don’t let questions like “is data science a good idea?” cloud your mind and impair your judgment.
What About Job Satisfaction?
Truthfully, job satisfaction depends on how passionate you are about the data science field. If your goals are clear, you will look and apply for jobs that match your work ethic and future growth opportunities.
With plenty of impactful opportunities in the industry, your data science journey will be thrilling. The data science industry is fast-paced. Unlike the research industry, where you spend five years to get rewarded, the data science field rewards as quickly as possible (typically within the first year).
Are There Any Growth Opportunities?
It doesn’t matter if you are in the academia-industry sourcing analytics courses online or lectures; you can easily find better opportunities in the data science world. Data science contains sub-categories of many other roles like an applied scientist, big data engineer, database engineer, data analyst, data architect, machine learning engineer, and more.
So, there are countless opportunities with sub-markets in it, unlike the academia-industry. With your academic background, especially in quantitative fields and data science, you will have a significant head start and a solid foundation to boost your career.
The field has better higher-income jobs than the academic industry. So, if you have the right skill set and potential, you can get a good job to gain your financial stability faster. Plus, you won’t have to leave the academia industry behind.
If you want, you can do research-focused jobs while being a data scientist. Other than monetary benefits, the industry is filled with new concepts. Every day is an opportunity to learn something new. You can take on potentially challenging projects, acquire new skills, and interact with intelligent people worldwide while working as a data scientist.
Challenges You May Face in the Data Science Industry
1. Job Security
Working for the private sector can take time to secure your job. Such corporations hire at will. This means they can terminate you at any time, for any reason (except for an illegal one), or for no reason without incurring any legal liability.
However, this won’t be a concern if you keep updating your skills, taking top-quality free data analytics courses online, and bringing success to the company. So, make your name in the company, and the rest will be fine.
2. Possible Toxic Workplaces
Not every company has a thriving, positive work culture. Some workplaces are toxic, with gossiping in the air and too much pressure because of work. Your line manager may be toxic - always asking for work, even after office hours.
Getting handed more work can cause burnout, resulting in ‘quiet quitting’. Or maybe your colleagues would be toxic. Working in such an environment can be impossible. So, make sure you choose a company with diverse work culture and flexibility.
3. Be Agile and Quick
Data scientist roles require individuals to be agile and adaptive to new situations and working environments. This can be hard for people. So, staying in this field can be difficult if you can’t learn quickly and show results.
Conclusion
Change is the only constant that the data science field requires. To move in the right direction, you can take help from a qualified mentor that’ll push you in the right direction. Overall, transitioning from academia to the data science industry is not something new or unconquerable that you can’t do.