Interview with John Cook: mathematical consultant

Highly recommend his blog [1] - where he often writes bite-sized math-y articles. I have personally benefited from it; I was looking for ways to sample quickly from a mixture of Beta distributions when I stumbled upon his post on the <i>Kumaraswamy distribution</i> [2], which takes on Beta-like shapes but has a closed form expression for the cumulative distribution function (CDF). The latter property makes generating samples from it convenient and fast.<p>[1] <a href="https:&#x2F;&#x2F;www.johndcook.com&#x2F;blog&#x2F;" rel="nofollow">https:&#x2F;&#x2F;www.johndcook.com&#x2F;blog&#x2F;</a><p>[2] <a href="https:&#x2F;&#x2F;www.johndcook.com&#x2F;blog&#x2F;2009&#x2F;11&#x2F;24&#x2F;kumaraswamy-distribution&#x2F;" rel="nofollow">https:&#x2F;&#x2F;www.johndcook.com&#x2F;blog&#x2F;2009&#x2F;11&#x2F;24&#x2F;kumaraswamy-distri...</a>

&gt; Once I started consulting, several of my initial clients offered to hire me as an employee; my backup plan was to pursue one of those offers.<p>I&#x27;ve been consulting for ten years in software&#x2F;AI&#x2F;data science. One of the largest difficulties is that many potential clients actually want an employee, not a consultant (perhaps hoping I&#x27;ll join full-time if it works out, similar to above). In fact, most people who reach out are only looking for employees.<p>Nowadays it&#x27;s also become more difficult to independently consult in California, since there are tighter tests for independent contractor vs. employee. Even forming a single-member LLC may not be enough to get around the distinction for some types of work. Due to this, one of my 5+-year clients was forced to reconsider our contract, and ended up only offering employment.<p>Supplementing income with part-time employment could be perilous for a consulting business (note: ianal, consult your own lawyer). For example, there is potentially an explicit &quot;duty of loyalty&quot; not to work with &quot;competitors.&quot; And, the IP ownership clause could include any work &quot;related to&quot; your employer&#x27;s business -- even when created on your own time.

I was excited to read this as someone with a mathematical background and is now an engineer and software developer. However, I think this just calls out all the open questions about this style of consulting and doesn&#x27;t answer them. How does one get clients, how does one keep a steady income, how to invest for retirement, how does one convince clients you have the right skills, how do you know you have the rights skills, etc.?<p>Also, there are conflicting answers in that he wanted better control over income than traditional employees but then later says income can be infrequent, saving is hard, and payments come late. I have none of those issues as a salaried employee and also have retirement benefits. He also mentions that finding work is no harder than finding employment but then later said that finding work is harder than doing the work.<p>&gt; Clients often need to have a conversation with someone who thinks like a mathematician. This means carefully defining terms and focusing on the largest ones, making implicit assumptions explicit, knowing when an approximation is or is not good enough, and so forth.<p>I love to see this mentioned, but in my personal experience, this has not been valued at all. I have tried it and discussed it, but nobody has appreciated it. This is really what domain-specific design tries to get at in software engineering, but almost no one practices it.

John D. Cook seems like the type of person who would inevitably rise to the top of their chosen profession, regardless of which path they took to get there. He is very intelligent, creative, and determined to do things his own way.

&quot;Academics are often disappointed if a solution is too simple because that means it might not be publishable, but private sector clients are delighted with simple solutions.&quot;

As a B-school prof, I followed a few consulting opportunities. Results:<p>(1) Not always easy to get paid.<p>(2) Medicine and some fields of engineering are recognized and accepted professions where both the professional and the customer know something about what to expect. Less so for applied math. In simple terms, so far applied math is not yet much of a profession.<p>(3) Really, all the business came via the B-school. But the academic, research university <i>culture</i> of the B-school regarded any consulting or applied work as neglect of research or teaching.<p>(4) Somewhere have to get past the norm that a pure&#x2F;applied math Ph.D. should not make money enough to buy a house and support a family. A lot of people with no graduate degrees, in nice houses, with late model cars, doing well supporting a family, are laughing at how <i>smart</i> math Ph.D.&#x27;s are. And, if business person X meets a pure&#x2F;applied math Ph.D., e.g., in just a business meeting, person X can resent that the Ph.D. may know some technical material they, person X, does not know and that might be important for the business of X. A person with cancer does not resent the knowledge about cancer held by an MD treating that person for their cancer.<p>(5) Broadly, a medical school is <i>clinical</i>, sees patients, and the profs, MDs, are expected to continue to practice their profession, that is, continue to see patients. Again, the usual research university math&#x2F;science culture would regard the <i>clinical</i> work as neglect of research or teaching, but, really, medicine is one of the most active and productive fields for research.<p>(6) At times there are opportunities, with eager, well funded customers, for computing with some applied math in US national security around DC. To be blunt, pure&#x2F;applied math in the research universities gets funded nearly only by the US federal government and for basically one reason, US national security, and because of some of history, cryptography and The Bomb, with some respect for applications of antenna theory.<p>(7) My view is that some guy in a <i>big truck&#x2F;little truck</i> business -- buy from a few big trucks, sell from lots of little trucks -- is right: That is, have a business, an actual <i>business</i>, with products and&#x2F;or services, customers, revenue, and earnings. For more, now, there may be good businesses based on computing and the Internet, for more than just Intel, AMD, Cisco, Qualcomm, Microsoft, Apple, Google, Facebook, and Amazon. And some pure&#x2F;applied math somewhere in such a business, likely programmed and buried somewhere in the infrastructure, might be a crucial advantage.<p>Else, what are we racing toward, a few really big companies making robots and everyone else with nothing to do?

He and Stephen Wolfram. Both same sort of style. Their math is more on the applied side than purely abstract.

His argument about employment is weird. I am 99% sure he could get paid more with less lead-chasing if he worked for one or more tech companies as a researcher, analyst, or developer. Maybe his consulting work is more <i>fun and interesting</i>, but “agency over income” is doubtful.