The usual apologies—or something like that—for the absence of entries of late but, well, I’ve been working, a lot, and since the Mission Statement of Parus Analytics—man, I can’t begin to tell you how many three-hour meetings, corporate retreat weekends with trust falls and consultants with really expensive business attire and hair stylists it took to settle on this! —is
We’ve got a radical approach to software development: writing code that works, more or less on time, and for the price quoted.
work takes priority.
Still, this month marks the completed third year I’ve been “feral” and if that transition had been a serious mistake, I’d presumably know by now. Since this hasn’t happened, a “Feral Plus Three” seemed in order. And meanwhile I’m going to be participating in a panel at the Society for Political Methodology meetings on non-academic careers, so I’ll use this occasion to write down the [largely stunningly obvious] advice I’d give to someone who is contemplating following this path.
But first, the takeaway, a caveat, and the context.
The takeaway is that when I published Feral (27,000 views and still counting), I got several nice notes from people saying they had done the same thing and never regretted it. Which has been precisely my experience, along with an increasing sense that if I hadn’t done this, I would have missed out on some of the most interesting times of my life. Moreover, while for very real family reasons I could not done this earlier, probably the optimal time would have been somewhere in the 50 to 55 age bracket. Carpe diem!
The caveat is that I’ve done this as a “data scientist.” Whatever the heck that is, but it seems to involve the same combination of social science expertise , computer programming, statistical analysis and machine learning  which previously defined me as an academic “political methodologist.” And at this point in history, the demand for data scientists appears to far exceed the supply, and provided you’ve got the requisite skills , one can set up shop as a data scientist with little more than a laptop and an internet connection. 
Finally, let’s be very clear that I’m discussing the prospects of establishing an on-going small consulting business intended to be sustained indefinitely, not a flash-and-burn start-up with aspirations to become a unicorn and for the principals to own—or at least lease—a Gulfstream G650 before the age of 30. The latter is for someone else’s essay, probably on LinkedIn.
No, I’m content to be one of the little mice down here in the weeds, not Bill Gates or Steve Jobs or Sergey Brin or Mark Zuckerberg or Peter Theil, but just part of one of the tens of thousands of largely invisible small shops that are driving the current technological revolution. 
So, seven suggestions on what should you consider and do to instantiate this.
1. Assess your resources and risk tolerance
Assuming you are leaving an existing secure career, before anything else, assess your financial situation  because compared to a tenured position in academia, you are moving into a much riskier situation.
I’d planned the “feral” move for about two years, and was certain I had in place funds to make it to full retirement age even if those plans went really badly. They didn’t—in fact I never touched a penny of those reserves, and have actually added to them—but the safety net was there. And like all safety nets, that allows you to take more risks, or at least turn down projects that don’t seem to make sense, and go through the inevitable period of experimentation that will be required before you really find the match between your skills, interests and the market.
Yes, risk: that’s what you are moving towards. In the absence of unethical behavior  the downside income risk of an academic career is almost negligible. However, the upside risk is also very limited—less so if you can skitter around getting outside offers, though at some point that accumulates issues, to say nothing of bad karma—and more generally, even if you are fabulously successful in generating external funding in academia, most of those marginal benefits will go, for example, to topping up the salaries of your so-called colleagues whose core competence (and life’s ambition) is making your existence miserable. And someone has to pay for all those deans, associate deans, assistant deans, deanlings and deanlets. For political methodologists, escaping this also means your summer salary will no longer depend on whether Senator Jeff Flake decides to pick up the red or blue light saber—and he is adept with both—when he gets up in the morning.
But if you currently have a secure job, be realistic about the risks: those positions aren’t called golden handcuffs for nothing. They really are handcuffs. And they really are golden.
2. Get thee to a tech hub
Contrary to what you are doubtlessly thinking, “tech hub” does not mean you are destined to life in a $4000/month one-bedroom efficiency somewhere within shaking distance of the San Andreas fault: In fact if you are planning to work for yourself or in a small group, that is probably the absolutely worst place you can establish yourself due to the cost of living. Those same issues limit the attractiveness of other major metropolitan tech areas such as Boston, New York City and the greater Tysons Corner metroplex.
Instead, you need to find some place which has a thriving tech ecosystem, the sort of place where, say, on a summer evening you might find 50 people showing up for a talk on the Python natural language processing toolkits spaCy and gensim. Said talk held in a cavernous room in a re-purposed Coca Cola bottling plant which now houses a huge German-themed beer garden with a bocce ball court and [of course] a high-end bicycle shop. Which is to say, Charlottesville, Virginia.
Which is almost certainly not on the popular radar screen for tech hubs, but it is one. [14a] And there are certainly dozens, probably scores, of other places just like this, probably most in or near towns with major universities.
So, how do you find these. <joke>Here’s the really bad news:</joke> you look for places where people, particularly young people with substantial amounts of discretionary income, which is to say programmers, really want to live. Paul Graham has described this better than I, but that typically means a lot of nice restaurants, a thriving music scene, and access to outdoor recreation. And brewpubs. And of course ethnically diverse and LGBT-friendly. Yes, this is really tough set of lifestyle constraints, but such is the contemporary world of data science.
Now, some of my younger data science compatriots—and yes, they are mostly younger—go one step further and say that a place isn’t really a tech hub unless it provides a situation where you can quit your job in the morning and have another by the afternoon. And if you are the sort of person who is likely to be needing to do that on a regular basis, you’ll probably want some place larger, for both the opportunities and, most certainly, the anonymity. But for the more occupationally adjusted, the lower costs and higher quality of life  in a smaller urban area probably outweigh the opportunities of a large one.
While you are looking, keep in mind that “business climate”—particularly for small business—is going to affect you, as I discussed earlier here. Pennsylvania’s small business climate, of course, is uniformly horrible, unless you are fracking. In contrast, as long as you can avoid their massive license raj , Virginia is quite small business friendly, and the differences in the costs of compliance are measured in hundreds of dollars (your money) and hours of time and frustration. Charlottesville’s 50% discount on the business taxes for high-tech businesses, software development included, didn’t hurt either.
In all honesty, however, we made the decision to move to Charlottesville—we had checked out a number of cities in driving distance of the greater Tysons Corner metroplex—not on the basis of the number of small software companies or the Virginia small business website, but rather when we walked into a coffee shop the morning after we’d been to a concert by the Hackensaw Boys at the Jefferson Theater and saw they had “cortado” on the list of coffee drinks, this when few places in the U.S. had even heard of that drink. A more pleasant experience than picking a few institutions in various Rust Belt hellholes and isolated 19th century agricultural rail hubs that have posted positions on the APSA jobs site and hoping one will deign to interview you.
3. It’s a business, but…no big deal.
Assuming you’ve already been doing independent consulting (and hence are accustomed to keeping accounts, filing Schedule C and the like), the shift to being a small business full time is modest, and after some initial efforts (incorporating an LLC, getting a bank account, getting Affordable Care Act and business insurance, a logo, coffee mugs) it largely takes care of itself. You’ll hear a thousand arguments from people who have never worked outside a large bureaucracy why this is really, really scary but in fact, people do it all the time: I’ve explored this in boring detail here.
You will, however, also quickly learn that while United States popular culture glorifies small business, the United States business establishment—in particular banks—absolutely hate it, and by inference, hate you. Fortunately you need very little capital to work as a data scientist.
And yes, Trump and Sanders are correct: the system is thoroughly rigged to favor large established institutions: for example it is estimated that it takes as long as ten years to become a prime contractor for the U.S. Dept of Defense. Never forget you are just a little mouse…but my, those dinosaur eggs are tasty.
For guidance on the nature of the contemporary tech business, start by reading everything Paul Graham has written. Classics of computer programming management such as The Mythical Man-Month and The Psychology of Computer Programming will assure you that all of the weirdness you are encountering in projects is the norm. Avoid start-up porn, portrayals of small business from Hollywood, management books displayed in airports, the “networking-is-everything” losers who write for LinkedIn, and, in spades, people who give TedX talks.
4. Get an office: physical space matters
Well, it does to me: I inadvertently ended up working from home for a month or so when I started, and found there were far too many distractions—grab something from the kitchen, weed the garden, don’t take a shower until noon—and I actively want the home/work distinction. This indulgence has quite consistently cost me about $400 a month (seems to be the magic number for both State College and Charlottesville) but it is worth every penny.
None of these spaces have been in conventional office buildings: As you quickly will learn, lots of residential structures in urban centers have been converted to office space, and your co-occupants are likely to be lawyers, accountants, financial planners, and—particularly—therapists of many varieties. These places are not necessarily advertised: use your social networks and walk around neighborhoods you’d like to be working in looking for “For Rent” signs in windows. In my experience, landlords like programmers: we’re quiet, don’t require parking for clients, and generally pay the rent on time.
Co-working has gotten a lot of press, but as a programmer-introvert, I found co-working space to be the spawn of Satan. I actually tried such an arrangement but realized after six months a lot of other people had looked at the option and no one else had taken it—if you can’t identify the biggest sucker in the room, it’s you—and meanwhile the guy managing the space had the affect of the doll in the Chucky movies, had fired everyone who was there when I’d first looked at the place and my desk was on the other side of some thin wallboard from a lawyer who would periodically go ballistic. I bailed—on the positive side, I was renting by the month—and now have a lovely space with big sunny windows a couple blocks away, the only slight issue being that I periodically find the microwave filled with peppermint-scented rocks.
5. Your team. Or not.
Paul Graham  makes the case that the most efficient programming operation—and this would certainly apply to a data science operation—is about a dozen people  with a diverse set of skills who completely trust the quality of each other’s work and generally self-manage. He further argues that only in these organizations is your income likely to be pretty close to your true marginal contribution to the enterprise: anything larger and some of that income is lost to management infrastructure, and other parts are lost to equalization policies.
That’s the ideal, rather than the route I’ve gone, which is nominally to work alone, though in reality I’m in almost daily email contact with one or more people in a geographically dispersed group of, well, about a dozen people with a diverse set of skills whose work I completely trust.
Were a suitable opportunity to present itself, I’ve no question that this cluster could work more efficiently were it focused on a single project and quite possibly (but not necessarily) in close physical proximity, but there is a core constraint one has to confront here: $100,000, which is roughly the amount of revenue you need to support every programmer. That is a high hurdle, and while I’m risk acceptant to some degree, I haven’t gotten to that level yet.
6. Keep three or four projects going or in the works
Almost all programming projects are transient—the entire point of the enterprise is to get something running that the client can take over—so you need to keep new ones coming in. It’s too early to say whether “data science” projects will be different but I’m guessing at the levels where this has been out-sourced, that may also be the case, though it may not be. 
A skill you will need to develop if you haven’t already is being ruthlessly realistic about estimating the time and effort required to complete a project: this is not just with respect to the total amount of time required but also the point at which you need to start wrapping things up—data science projects tend to be very open-ended—so that you can finish things cleanly with good reports and documentation, and the latter tends to take a lot longer than you think. Most academics have a heck of a lot of unused time on their hands: you won’t, and rosy scenarios are not your friend. And once again, remember that despite everything you read in the start-up porn, “fail early, fail often” only applies to white males from a tiny number of elite schools.
Even if you are primarily working in R and Python, which you presumably will be. You may not need these other languages to build your own tools (though you may) but it will give you wizardly credibility: people—for example, your mother—may not know what data science is but they know what a web page is.
Beyond that, look forward to a constant effort of keeping your skill set up to date and trying to make those critical decisions as to which of the new technologies is worthy of your investment and which in a couple of years will have been relegated to the [unbelievably huge] scrapheap of technological history. You will live not in moldering library stacks and stifling seminar rooms , but by GitHub and Stack-Overflow, Slack and Google Hangout, Dropbox and Amazon Web Services. Open source and open access, always .
And then enjoy the wonder of a world where you can operate at the cutting edge of your profession using nothing but your wits and an investment in a professional-quality laptop.
Five out of my last seven political methodology students at Penn State have chosen to go into non-academic data science positions. Presumably that means their training at Penn State is either really bad, or really good. The fact that two of those placements were at Google and Apple, which have thousands of applicants for every position, I’m inclined to the latter interpretation.
Granting that I am an egotistical sonofabitch embedded in twenty-first century United States culture, the single biggest benefit of going feral is knowing that I’ve now gone for three years supporting myself in the same professional lifestyle I had when supported by a large institution but I’ve done it on my own: no one is hiring me because I’m affiliated with X. Priceless.
Beyond the Snark
Paul Graham’s blog: http://www.paulgraham.com/.
Paul Graham’s Hackers and Painters :http://www.paulgraham.com/hackpaint.html (hey, give the poor starving author a break: Quora says his net worth is only somewhere between $260M and $1.4B.)
Another recent take on non-academic tracks for political methodologists: Andrew Therriault Finding a Place in Political Data Science (PS, July 2016) http://journals.cambridge.org/download.php?file=%2FPSC%2FPSC49_03%2FS1049096516000925a.pdf&code=6b6b49ff6c2cd9af6798fcc5c0bfb3b2.
Joel Spolsky on why programmers need offices with walls: http://www.joelonsoftware.com/articles/fog0000000043.html
Science (20 May 2016: Vol. 352, Issue 6288, pp. 899-901): Preprints for the life sciences http://science.sciencemag.org/content/352/6288/899.full
The Mythical Man-Month: https://en.wikipedia.org/wiki/The_Mythical_Man-Month
The Psychology of Computer Programming: http://www.geraldmweinberg.com/Site/Programming_Psychology.html
Why it’s better to let cougars kill pets and joggers than to allow deer to kill motorists (and eat hosta): http://www.nytimes.com/2016/07/19/science/too-many-deer-on-the-road-let-cougars-return-study-says.html (Bambis, we hates them forever)
Various previous mouse entries relevant to this topic:
Boring mechanics of setting up a business: The Mouse Goes Into Business : https://asecondmouse.wordpress.com/2014/12/28/the-mouse-goes-into-business-2/
Banks hate independent contractors: Mr. Bernanke’s mortgage: https://asecondmouse.wordpress.com/2014/10/04/mr-bernankes-mortgage/
42-page rant on what’s wrong with the contemporary academic system and why it isn’t going to last: http://7ds.parusanalytics.com/7DS.University.chpt.pdf
1. : Okay, so I can: none… Like you hadn’t guessed.
2. Even with those constraints, that’s about the point where I shifted from a conventional teaching track to a research-oriented track: I’m pretty sure the last time I taught a full course load was in my late 40s.
3. You will never realize just how much you know about human psychology and organizational behavior—any humans, any organizations—until you start working with computer scientists. To say nothing of research design.
4. The fourth common component is visualization, though I don’t really have skills in that area and thus far they haven’t been required. Though there is also something to be said for the definition cited by Therriault: a data scientist is someone who can’t write software as well as a software developer or do statistics as well as a statistician, but nonetheless can do both.
5. Or, let us be realistic, with the current demand for people who call themselves “data scientists”, even if you don’t…
6. If your core academic competency is writing jargon-laden critiques of why quantitative models cannot possibly work, you will probably need to continue grading blue books indefinitely, and you might want to just stop reading at this point lest you become very, very sad. No, wait, such people don’t get sad, just outraged. Which, of course, is the same thing.
7. So stay away from the start-up porn, or at least don’t take it seriously: Beyond the fact that the vast majority of startups fail, even in the ones that succeed most of the employees of startups don’t get the benefits, and can be left with burdensome tax obligations after those highly valued unicorny—or is it unicornish?—stock options decline in price. But again, that’s someone else’s essay. Just be cautious, okay?: there’s a critical difference between getting out of the box and going out of your mind.
8. And discuss it with your partner, if such an entity is in the picture. Avoid those “Honey, I’ve decided to go into business for myself!” “Oh, so you’ve been fired?” situations. Though my wife was amused to watch the reaction of people when they said “Your husband retired” and she corrected “No, he quit.” Invariably, people—granted, this was in a company town—responded with variations on “But no one quits a tenured job!” Yes, they do.
9. As for non-tenure-track positions in academia: hmmm, are those in the fifth or sixth circles of Hell? <TRIGGER WARNING!!!> To paraphrase Denis Diderot—hey, man, wasn’t he a midfielder on Cameroon’s World Cup team in 1990?—academia will be free when the last associate dean is strangled with the entrails of the last journal publisher, dumped in the ruins of the last student aquatic center and buried by a press-gang of the last post-modernists </TRIGGER WARNING!!!> I digress.
10. If you are a 20-something reading this, you probably don’t need to plan quite that far ahead.
11. As well as dealing with payment delays that can run into months. Though as we’ve entered the era of zero to negative interest rates, I’m finding my invoices are being filled noticeably more quickly. Funny, that.
12. Though, after tenure, without much required in the way of a work ethic.
13. …subsidizing loss-making athletic programs; paying for the insurance, liability claims and golden parachute payouts of disgraced administrators of profit-making athletic programs…I digress…
14. A speaker I recently heard who heads a Charlottesville-based engineering startup quite possibly heading for unicorn territory put the issue succinctly: “Silicon Valley has the best tech ecosystem in the entire world. But unless you are in the top 1% of income, it is a shitty place to live.”
14a. I didn’t actually appreciate Charlottesville’s software situation until I attended one of my first data science meet-ups and casually mentioned to some stranger that Parus Analytics might be hiring a Python programmer at some point. The gentleman, exercising those social skills for which programmers are so famous, gave me a look of disgust and said “Well, good luck with that: no one around here can hire Python programmers because there’s too much demand for them.” Well…I suppose that’s an issue if you are trying to hire a Python programmer, but quite a different situation if you are already a Python programmer.
15. If this is your planned career strategy, taking a few pointers from the Federal witness protection program probably wouldn’t hurt either.
16. We recently returned for an extended vacation in the Bay Area, where my wife had worked for about 15 years in the 1980s and 1990s. Our conclusion: the restaurants in Charlottesville are better. And saving $2000 a month in housing costs buys a lot of restaurant meals.
17. For example the regulation of ginseng dealers. Because as political theorists from Montesquieu through Weber to Skocpol have emphasized, one of the core functions of the modern state is to protect the citizenry from the threat of substandard ginseng.
18. Years ago I saw an advertisement in some airport with a picture of the stereotypical evil besuited banker, cigar in hand, saying “You don’t need a small business loan, you need a job!” Yep, that’s the attitude. I’ve discussed this issue in more detail here: Apply for a mortgage as a sole proprietor and, whatever your assets, you will be politely but firmly told to go to hell. Though this will be blamed on Obama, Clinton, Warren and the Illuminati. Nonetheless, I own a house. With deer.
19. To whom I owe at least half of the ideas in this essay.
20. The building where my office is now located also houses a web developer, at least three psychological therapists, one Rolfer, one hot-stone massage therapist, a small trade journal, and a couple lawyers. Adjacent properties—all converted residences—have a remarkable number of hedge fund managers, a Sotheby’s office catering to those hedge fund managers, still more lawyers (we’re near the county courthouse), and a hospice.
21. Based on having now rented four spaces, two of which I was very happy with and two which didn’t work out, here are the criteria I use:
- About 200 square feet with walls and a door: I like to sprawl.
- Not too many people around, but not too few
- Kitchen (but I don’t use conference rooms nor teleconferencing facilties)
- High-speed internet
- Walking distance from home and walking distance to a coffee shop (or in the case of the Charlottesville pedestrian mall, six coffee shops)
- Weekend parking
- When furnishing your new digs, Habitat for Humanity ReStore outlets and Goodwill are your friends: you can get amazing stuff there. It’s all zero-sum on your money now. Put Lowe’s in the mix as well.
22. Did I mention that you should read Paul Graham?
23. Roughly the size of a modern infantry squad. And a Roman infantry squad. And a Mongol cavalry squad. And a baboon foraging party: we’re hard-wired for this number.
24. I’m guessing small groups also do a lot of income equalization but they are able to much more effectively monitor and sanction slackers.
25. The median salary of a programmer in Charlottesville is reportedly $76K—presumably not including benefits—so adding those benefits and even minimal administrative overhead, $125K to $150K annual revenue is probably more realistic. So at the self-managing baboon troop level a project would probably need a minimum of around $1.5M in annual revenue. An organization at the baboon level should also be able to get by with an overhead rate of 10% to 15%, substantially less than that of larger organizations, and this will sometimes, though not always, provide a competitive advantage.
26. This actually gets to what I regard as one of the two most important economic (or political-economy) questions of our time (the other being, of course, the rise in income inequality): what sort of long-term balance will be achieved between the incredible efficiency of baboon-troop-sized small enterprises and the oligopolies of contemporary “bozo capitalism.” The disintermediation made possible by new technologies is reversing the classical Coase transaction cost justification for the corporation, but at the same time corporate power is being concentrated at levels not seen in more than a century. Where does it all end?
27. You will also find that you shift from placing a premium on the multi-tasking required in academia—and pretty much any large organization—where you rarely have large blocks of focused time, to highly focused uni-tasking where your objective is to be at the production-possibility frontier of quality vs time. Observed from the perspective of a small group where your income is entirely dependent on what you can produce, the amount of time wasted in the endless pointless meetings characteristic of large organizations is jaw-dropping.
28. Or, god forbid, reading proprietary social science journals: Trying to do research reading the published social science literature is like trying to drive by looking through the rear window using a telescope. For example, an article I had coauthored was recently linked from an interview in the Washington Post. Which was really cool, except that the original idea had been drafted—I remember this very clearly since it was during PolMeth XXIII at UC-Davis—a full ten years earlier.
29. There is nice recent discussion in Science on the huge advantage computer scientists have gained by emphasizing open-access pre-prints (and arXiv specifically) over proprietary journals. Science has the sense to leave this open-access rather than pay-walled. At least at the moment. Thus depriving us of an opportunity for deeply ironic snark.