Myth #1: You can only do research in an academic setting. Not true. There are plenty of research labs owned by big and small companies and organizations, including government, as well as abroad. In my case, I own and manage my self-funded research lab, publishing in my own niche media outlets (see here.) At some point I run a VC-funded company, and VC’s like to hire PhD scientists as co-founders.
Myth #2: The best outcome is to become a university professor. Not true, very difficult these days, and in my case (independent researcher) I have more flexibility to choose which projects I will work on (not influenced by grant hunting or politics) and produce high quality output — sometimes even ground-breaking — accessible to a large audience, as opposed to esoteric papers read by very few people. I will go as far as to say that my job security and revenue, as an entrepreneur, is better than that of a successful tenured professor.
Myth #3: You are bad at managing a business, forget about it. Not true, you can even start a business when working on your PhD. Not all of us are geeks. Not only did I become an entrepreneur without gaining an MBA, but I do better than most of my MBA peers, as I learned how to run a business (and ended up loving it) from scratch. The result is that my competitors — who hold an MBA — have learned old stuff at school, and lack the original ideas that I have to compete with me. I am eating their lunch. It really helps to be a self-learner, but any PhD worth her grain of salt is a self-learner.
Myth #4: You are not a very social person. Not true for many. And indeed to succeed as an entrepreneur, it helps to be very good at making important, relevant connections at the right time (quality better than quantity here.) It is doable, but not a skill you learn at school. Making efforts to be well-known in a hot field, also helps. As well as “planting seeds” that can go dormant for years but will develop in a big tree at the right time. In my case, I was able to transfer Internet fraud detection expertise (even though my PhD was about image processing) into working for Visa in credit card fraud detection, as a consultant. And later received VC funding (it takes some efforts to get; the right connections help) back again working in Internet fraud detection (traffic quality scoring.) Now image processing is hot again!!
Myth #5: You will either work all your life on stuff related to your PhD thesis, or otherwise have miserable jobs that you hate. Not true, but to escape from this dilemma, you need to embrace and love change (see also myth #4), be passionate about what you do, and adjust your passions over time. I started as a statistician, then data scientist, now I am deeply interested in number theory (with applications to hot problems such as Blockchain.) All of this while pursuing business opportunities to the point of creating and operating (with love) my own successful companies. I also tried to find the right partners for these endeavors (see myth #4 about connections.)
Related Article:
For related articles from the same author, click here or visit www.VincentGranville.com. Follow me on LinkedIn.
DSC Resources
- Subscribe to our Newsletter
- Comprehensive Repository of Data Science and ML Resources
- Advanced Machine Learning with Basic Excel
- Difference between ML, Data Science, AI, Deep Learning, and Statistics
- Selected Business Analytics, Data Science and ML articles
- Hire a Data Scientist | Search DSC | Classifieds | Find a Job
- Post a Blog | Forum Questions