How do you make the transition from a career in academia to a data professional? Many students at The Data Incubator (TDI) say that was their first hurdle when deciding if they were ready to apply.
The scariest part is simply leaping into the unknown, which is why we’ve asked TDI alum, Newton Lee, to share his experience and eliminate some of the ambiguity.
Most importantly, he’s been in your shoes: staring at a big idea but uncertain how this journey would impact his future.
Newton is currently a senior machine learning engineer at the Twitter cortex, where he works as the technical lead for the machine learning pipelines team.
Previously, he was placed by TDI at Crunchbase as a data engineer, where he built the news ingestion pipeline that associates news articles with companies and people. Newton shares seven lessons he learned while working through the process of transitioning out of academia.
Lesson 1: Employment in Academia is Highly Competitive
I had a pretty bad academic resume. Mainly, I didn’t publish anything. So, I was definitely in the statistics of unlikely to land an academic job, and certainly nothing on the tenure track. TDI was my way forward, and I’m glad to have gone down that path.
Out of the 16 individuals who graduated the same time I did, only two managed to get an academic job even though most of us attempted that path. Careers in academia are possible, but the odds are stacked against you.
Lesson #2: Ask Yourself: “What do I enjoy?”
The question you need to ask yourself before deciding to stay in academia or leave is “What do I enjoy?” or “What do I feel is missing?”
When I was doing research, I was trying to read many papers on how to do specific analyses of reinforced concrete. After implementing the code, I was trying to understand what I enjoyed about the work.
Did I enjoy reading the papers and understanding the theory, or was it the computational part of implementing code and seeing it run? In the end, I concluded that it was just solving problems using computers. That was the thing that interested me.
Lesson #3: Teaching Is Still Available in the Private Sector
Many larger companies like Twitter have internal programs like Twitter University, which allows you to teach as if you were in academia. There are people entirely dedicated to these programs, so if you’re an engineer or data scientist, you can sign up to be a teacher for specific courses and have a class with a curriculum to follow.
Lesson #4: I Found More Support Outside of Academia
When I was doing research, I coded something and ran the analysis, and the results weren’t expected. So, I talked to my advisor about it, and he said I was the only one who knew how to code. I was on my own. That’s how it can be in academia.
In industry, it’s way different. You give status updates every day. And there’s a word for my previous dilemma called a blocker. I was just stuck on one thing.
At the companies I’ve worked for, the whole team works together to try to unblock you. It’s wonderful having a support structure to help you solve problems.
You can hear more about Newton’s story in our Navigating Your Career Transition Out of Academia into Industry webinar!
Lesson #5: I Discovered Work-Life Balance
One of the things that surprised me was when I told a manager at Twitter that my project was moving slower than I had expected, and I was going to work on it over the weekend to get it done, he stopped me.
He said, “No, I don’t want you working over the weekend. Spend time with your family; I don’t want you to burn out.”
I don’t think those are words you’ll ever hear out of an academic advisor. You’re just going to hear, “We need to get this research done.”
Lesson #6: Your First Job Doesn’t Have to Be Your Dream Job
I think getting that first job is the hardest thing that you can do. I applied to dozens of companies for my first job, and most didn’t even respond to me. After working at Crunchbase for half a year, I started getting recruiters contacting me, cold calling asking me to work for their companies.
The recruiter at Twitter would have ignored my resume if I didn’t have Crunchbase under my belt.
Lesson #7: Investing in Yourself Is Never a Waste of Time or Money
Investing in yourself is essential. You want to set yourself up for success in your transition, and getting certified through TDI is a great option.
There’s nothing like getting an extra credential to boost your competence. You can look at job postings to see what kind of experiencing credentials companies look for and go for it.
It helps to know that your skills are cutting edge. You should be competent and make an impact on day one.
Are You Ready To Take the Leap?
At TDI, we’ve developed an ebook that outlines the process from start to finish for landing your dream data job. Keep learning about how to transition out of academia by downloading your copy of the ebook.
