Once you have acquired sufficient expertise in the field, you may wonder what the best option for your career would be. Do you take the safe path (i.e. a 9-5 job), the more adventurous route (i.e. a start-up, your own or someone else’s), or something else altogether (e.g. consulting)? Whatever the case, this is something to consider sooner or later and no book is bound to give you the answer you need (though there are good books out there offering general career advice for data scientists). The best career option for you greatly depends on your level of expertise and your ambition. If you have a lot of the former but limited supply of the latter, you’d probably opt for consulting as it is a career path that is highly competitive, so anyone who is merely competent is bound to struggle. That’s quite different though if you have a consulting company, which is more akin to entrepreneurship than anything else. The start-up option is more suitable for you if you are both an expert in your field and ambitious. The long hours, combined with the inherent uncertainty of the situation, make it highly unsuitable for people who just want to make a living. Besides, most data science start-ups try to break new ground, so it’s definitely not an option for the faint-hearted. If you in the beginning or the middle of your career and what you yearn for is a good benefits package, so that you can buy a house or something, then the 9-5 job option is the one for you. Who knows, if you are hard-working enough, you’ll get promoted at one point and be able to fetch a higher salary, one comparable with the money of the other career possibilities. Working in a large company is a somewhat different case, since such an environment tends to attract data scientists of high expertise, though their ambition may still be limited. Of course, an environment like this is extremely competitive and challenging in many ways, which is why after a few years you may decide to do one of the following: you may either leave and work in a smaller company so that you can attain a steady salary to pay your mortgage, or you may start your own company (something quite common among the more adventurous data scientists). Whatever you decide, it’s important to remember that there is no future-proof option out there. Even full-time employees in a company are bound to outlive their usefulness, in which case they may make you redundant or more you to a role that has little impact or prospects. Also, choosing a career path in data science that makes sense financially, may not be congruent to your growth as a data scientist. Because, contrary to what many people think, your professional prowess has little to do with the number of years in the field, or your familiarity with what’s popular in the market now. That may land you a 9-5 job, but that will not make you a better data scientist necessarily. This, however, is a topic for another blog post. Having been in pretty much every one of these work situations, I can say that at the end of the day what matters is what makes you happy. If you look at Mondays with dread, maybe it’s time to reconsider your career choices. If, you are like me and can’t wait for the work week to start, then you’re probably on the right track, career-wise. This doesn't mean that you should become complacent though. What’s good for you now, may not be optimal for you in a few years’ time, since new data will have presented itself.
3 Comments
9/5/2017 02:50:15 pm
What is the value of a certificate in data science from, say, metis or Galvanize?
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Zacharias Voulgaris, PhDPassionate data scientist with a foxy approach to technology, particularly related to A.I. Archives
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