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You may even call it post-doctorship, as the level is beyond the traditional PhD degree. It is not a degree, not competing with university programs, but instead, akin to a fellowship or apprenticeship to learn doing state-of-the-art applied research, discover ground-breaking results or applications, and translate your discoveries into seminal material suitable for a broad audience. It is intended for professionals with substantial experience, perhaps to people who already have a PhD in a different field. It is mentored by well connected, world-class recognized scientists (not necessarily affiliated with a university) with broad domain of expertise in many environments. The focus is on real-world problems and applications to help you get a high-level position in the industry or as an independent researcher.

The idea to create such a program stems from the fact that a PhD degree is sometimes perceived negatively when looking for an Industry job, and some candidates hide it in their resume. This is because a PhD degree is supposed to prepare you for Academic research, but due to the large supply of PhD's and a shrinking job market for tenured positions in Academia, many are left in precarious situations.

Source for picture: Women in data science

This doctorship is designed to make you a leading scientist in the Industry, to become for instance, an executive data scientist or chief scientist. It does not involve writing and defending a thesis, nor publishing esoteric papers in scientific journals read by few, but instead to quickly disseminate your research, explained in simple English, to a broad audience of practitioners.  For instance, possibly to attract VC funding if you want to create a start-up out of it. The standards are by no means inferior to that of traditional PhD programs, they are just very different. The length of this "mentorship" could be as short as two years; it could be carried out part-time, remotely, while having a full time job at the same time.

Features of the Proposed Doctorship

  • Short duration (2 years)
  • Publication in niche media outlets (like DSC), not in scientific journals
  • No teaching load
  • Done remotely, part-time
  • Cross-disciplinary research
  • Not attached to a university program
  • No thesis, no defense
  • Focus on Industry problems
  • Research not influenced by grant money or politics
  • Candidate gets an apprenticeship in the corporate world, related to her research
  • Not a degree
  • Not meant as a substitute to PhD programs

Example of Research 

I have one example in mind. This is what I would offer if I can find the time to start such an endeavor. The research in question is at the intersection of data science, dynamical systems, stochastic processes, computer science, and number theory, with applications to cryptography, Fintech, Blockchain, security, and high performance / high precision computing. Side projects could include the design of continuous random number generators, replacing standard statistical tests and p-value by better tools, or proving that the digits of some mathematical constants, are randomly distributed (this would be a fundamental result.) See here for details. I believe this research could lead to ground-breaking discoveries and nice applications.

I don't even have a PhD in data science, such PhD's did not exist back then. Instead my PhD was in computational statistics. Do I qualify to run such a program? Of course it is not for me to answer that question. You can check my career path here and judge by yourself.

The problem is, how many qualified experts are willing to take the challenge to offer this type of mentorship? How many professionals are willing to join such a program? Are there any companies interested in joining as partners?

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Comment by Jess Stahl on March 28, 2018 at 7:29pm

I think many professionals would be interested in joining the program.  The opportunity for mentorship, industry experience, and potential VC support is highly appealing.  I think the level of professional experience can be a bit confounding.  Data science focused MOOCs and nanodegrees are usually geared towards beginner-intermediate level without much advanced level resources beyond that.  Bootcamps that are associated with industry connections (e.g. job guarantees, Data Incubator) tend to want participants to enter the program nearly "job ready" as data scientists already, so I've never quite understood why people with that skill level would attend versus seeking data science work directly.  In other words, its a matter of determining the right professional level for participation where there is enough ability to engage in meaningful data science work but not so skilled already that the room for growth is excessively narrow.  Another complication for those wanting to enter the field of data science is actually knowing when you ARE sufficiently qualified to engage in useful work.  From the "outside", as a newcomer to the field, the list of competencies can seem nearly endless.  I think it's possible to keep learning for a very long time and not realize when you are "there" (qualified" as a "real" data scientist).  The type of program you describe is not possible to implement through universities and I would not recommend that academia even attempt to design such a program and I say that as an experienced academic administrator.

Comment by Vincent Granville on March 28, 2018 at 1:25pm

Hi Dan,

It is not a degree. I see it more like "I worked for 2 year at the DS research lab at X (say Facebook) and was mentored by Y, working on these ground-breaking concepts Z" where Y (the mentor) is a world renowned data scientist, preferably outside X (the partner company.) A Candidate successfully going through this will never have to apply for a job for the rest of her life. Jobs will come to her.

My example (the project that I have in mind) might be peculiar in the sense that it is both applied and theoretical simultaneously, but in most cases, I see it as mostly an applied program.

I am not sure whether the word "doctorship" is the ideal word, it definitely conveys the idea that it is about serious research and not an internship or a data camp, yet it is not a PhD. An analogy could be "Chief scientist in residence", the organization behind the program being called an "incubator."

The funding might be the biggest challenge. If I was the mentor, it would also benefit me and DSC (great articles published on DSC as a result, the ability for me to complete some great projects that I will probably never be able to finish myself alone) and thus I would not be paid. I just need to find the time. I could see VC's interested in the partner company X if it is a start-up created by the applicant, explicitly for the doctorship purpose (that is, the candidate would be VC-funded via the startup.) And getting accepted in the program would be about as difficult as getting VC funding (I actually did it a while back), and targeted to similar applicants.


Comment by Dan Butorovich on March 28, 2018 at 11:28am


You stated: "The goal is very different and definitely business-oriented (and also allowing people to work on projects that no grant will ever fund), and the means are very different  too (part-time, remotely, no teaching load, no defense -- instead you spend all your time on productive research, not unlike some post-doc programs, which is why it is much shorter.) " 

Two things: This seems akin to an MD program where it is entirely focused on gaining practical knowledge and application vs PhD which is focused on generating new knowledge and expanding theory. Second, without some form of accreditation, or general standards to evaluate competency at the end of the process, how can you grant a degree? Anyone can print a diploma, but without industry or academic certification it has no intrinsic value as a doctoral "degree" and it wouldn't be recognized anywhere. Not saying the idea is bad, it just doesn't seem practical in terms of actually being a doctorate, unless you go the route of something like an MD or other practical doctorates.

Comment by Dr. Richard J. Ferner, Jr. on March 28, 2018 at 10:31am


Another option, in terms of practical studies, would be an open source initiative. Check this article from Forbes ( If you want to solicit data from government sources, consider the Open Gov initiative ( Thank you.


Comment by Angie Williams on March 28, 2018 at 10:22am

I am very interested please let me know what I need to do to apply.

Comment by Vytautas Duoba on March 28, 2018 at 10:21am

Superb idea, especially if reasonbly priced. Some of the on-line degrees I have explored have very heavy price tags.

Like a regular PhD, such a program should be demanding and require, deep thinking and some originality, but not restricted to "academic" originality.

There is some academic scepticism about the worth of MOOC-type learning (which I do not agree with) so calling the program something other that Doctorate(ship) or PhD might be wise. Perhaps instead of trying to be a cheap version of regular uni campus courses, online learning should break away completely and set up its own standards and accreditation body. 

Comment by Nikita Ray on March 28, 2018 at 10:06am

This would be a great program. Many of us in the corporate world do not have the time commitment that a traditional PhD demands. We work on real world problems and a program that could cater to that segment of the population would be great. I'm definitely interested. 

Comment by VENKATA KRISHNA KUMARI GADDAM on March 28, 2018 at 9:59am

This is great idea... interested.please let me the process n qualifications.

Comment by Edwin da Rocha Isensee Neto on March 28, 2018 at 9:56am

Interesting and interested.

Comment by Dr. Richard J. Ferner, Jr. on March 28, 2018 at 9:46am


Perhaps your proposed program can seek to affiliate itself with corporate sponsors such as IBM, SAP, Oracle, Microsoft, Tableau and SAS. In terms of support from academia (if essential), a number of leading edge universities could be considered. If you want to establish connections with industry educators - perhaps a reputable coding academy is a good place to start. A good example would be the WOZ U (  Thank you.




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