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...That is the question.

 

Further study often seems the most appealing route to go down, and for many companies out there it’s often heralded as a must have for data science, but it isn’t always so and isn’t always pivotal in advancing your career.

 

To Ph.D.

 

A Ph.D. is your own original, unique research into something not necessarily covered from that angle before. The content of a data science Ph.D. should showcase new findings in the field that will make an impact, or contribute to a particular subject. A lot of people pursuing Ph.D.s are driven by a passion for their area of study, more than thinking of a specific role they can enter into afterward. They can take a long time to complete, so having a particularly keen interest in the subject, and passion in the field will drive your success. Ph.D.s are also a gateway into being published at top conferences in your chosen field, like ICCV (International Conference on Computer Vision), NIPS (Conference on Neural Information Processing Systems) and ECCV (European Conference on Computer Vision) to name just a few, which undoubtedly has a huge impact on a researcher’s career path.

 

Carrying out and writing about such in-depth research shows your ability to think critically about problems and how to provide solutions; researching new algorithms or improving existing ones. It often shows that you’ll be able to push the boundaries of what a company is doing once you enter into the industry. These are attributes desired by companies as they look to handling growing big data sets and solving even more complex problems.

 

Not just this, but research gives you an upper hand when it comes to fulfilling the demand for data scientists that can tell a story – i.e communicate at a higher level, their data insights within companies. Having a deeper knowledge of methodologies and the foundations of data science, you’ll typically exhibit a deeper understanding of theories and work using these, rather than applying algorithms from other sources.

 

Data Scientists holding more specialist Ph.D.s such as computational linguistics, computer vision or Artificial Intelligence can often command a higher salary in relevant industries, as well as the ability to enter a research position in your specialist field.

 

 

 

Not To Ph.D.

 

You may believe that Ph.D. candidates will always have an advantage when applying for roles, but that is not so.

 

It all depends on the type of career you want to pursue and the type of projects you want to work on as many data scientists have fruitful careers applying methods and algorithms rather than deeper research. It’s completely plausible to have a successful career in data science without a Ph.D.

 

Working your way up in a commercial role for example as a data analyst, you get the chance to work with data scientists, from whom you can build on your own skills and experience. With the right focus, you could soon find yourself a Data Scientist down the line. You’ll be more focused on applying current methods to solving problems and also have the opportunity to develop new algorithms.

 

If you are applying machine learning to a problem, you’ll need working knowledge of algorithms however, you’ll be more concerned with how to use it to provide a solution to what you are working on. With a focus on broader concerns surrounding the data, like its source, validity, how to format it, mining, or analyzing.

 

A Ph.D. is not necessarily indicative of a candidate’s ability in finding solutions to business problems. Engineering roles for example often prefer industry experience and hands-on coding more suitable than years of further study. If you are a Masters grad and seeking to begin your career rather than undertake a Ph.D., it is definitely worth gaining exposure in a particular industry to kick-start your commercial career. 

 

There is no right or wrong to this, and there are some fantastic data scientists out there who do not have a Ph.D. As with most things, it comes down to personal preference and what type of career you want to pursue. Know your strengths and play to them.

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Tags: big, career, computer, data, eduction, further, mathematics, phd, science, study

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Comment by Georges Grinstein on October 26, 2017 at 5:05pm

All comments below are correct. But I have always told my students that a PhD also offers easier mobility. It's a door opener and an accepted easily presented credential. It's a statement that you have achieved the highest level of education in your field and assuming your thesis is reasonably novel (usually is) that you're creative. What you do with it is up to you. Your starting salary typically will be more than an MA or BS and will eventually quickly catch up to the "lost" money during those 4 years. Most PhD programs will offer you reasonable funding, have you attend conferences, present papers, and you end up a part of an exciting community and learning a great deal (collaboratively). 

Somethings you should ask yourself: are you good? are you determined? how important is the degree for you? 

Finally - almost all my past students that have had PhDs are in industry, very few in academia (over 40 in total). Some were in startups, some in big companies (all the big names) and quite a number high up in management. It's their personalities and abilities that got them there. The PhD was a small part - it kickstarted them. I've had many who only have an MS degree (over 200) and they're doing quite well. Even several of the BS only are doing well. 

And most of all - it's quite satisfying as all of my students will tell you and a few of those that did not go on, stopping at the master's, regret that decision. I have lots of stories about that. So it's up to you - what do you want?

Comment by Bill Bentley on October 26, 2017 at 10:09am

My rule of thumb has always been that if you intend to teach at a university or do research in the private sector or have a need to have a very deep specialty, a PhD is a good investment and for some things, like university teaching, mandatory. In most of the commercial sector is is not only not necessary but can be a detriment. There are quite a few folks in management who equate a PhD with 'studying instead of doing', it's not fair but it is a common perception.   We have plenty of ways to deepen our knowlege besides spending an extra four years getting a PhD.  Consider the ROI also.  Even in academia, tenured spots are getting rarer all the time with relatively low paid adjuncts bearing the brunt of many workloads.   Losing four years of income to get a university teaching credential that is not sure to pay off is 'iffy'.  I'm sure someong here knows the actual statistics about that!  :)

Comment by Vincent Granville on October 26, 2017 at 8:03am

You can do PhD-level research in your spare time, outside Academia. Sure you won't get a diploma, you won't be published in traditional journals, but it can be a lot of fun and you may even reach out to a much broader audience. I publish all my research articles outside Academia and have created my own private research lab. One advantage is that I work on the projects that I want, rather than projects funded by grants, and I have no political pressure that influences my results. Another advantage is that my research lab is well funded, not depending on grant money. And 5 years ago, I granted tenure to myself!

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