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?

Related article

• 5 Myths About PhD Data Scientists

For related articles from the same author, click here or visit www.VincentGranville.com. Follow me on LinkedIn.

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