You know who you are. You’re a Data Scientist.
In interview rooms across the world, fat cat executives are pushing contracts under your noses with extortionately high numbers on them. What a time to be one of a few doing backstrokes at the world’s most exclusive pool party, right!?
What happens when other bright academics, who stand outside with noses pressed up against the glass, get bored, rush the gates and start doing huge running pool bombs? One only has to look at the statistics at the growing numbers of governments and businesses funding universities to teach Machine Learning or the accessibility of online courses and competitions to see how this is becoming a more accessible and inclusive market place.
Economist, Tyler Cowan once said; “Food is a product of supply and demand, so try to figure out where the supplies are fresh, the suppliers are creative, and the demanders are informed.”
The same can be said about Data Scientists. Businesses are becoming more informed about the potential of Machine Learning. When these businesses demand the skill, the supply must be met at any cost. Many businesses are smart and they’re flooding billions of dollars into closing the skills gap so it’s only a matter of time before the next generation of Data Scientists emerge.
So, how do you ensure you remain afloat on your inflatable crocodile with your Piña Colada in tact? Simple really, you have to diversify…or drown. Make yourself futureproof now. Continue pushing yourself in new ways, to ensure you’re not left behind.
Here are a few suggestions:
Become a He-Man/She-Ra Coder
One of the current trends we’re seeing is the growing demand for Data Scientists with production coding experience. For some businesses, proof of concept coding is great. For others, the ability to write the code that takes it into production, is even better! Some businesses that don’t have engineering teams tend to prefer this option. Other businesses just like to kill two birds with one stone made out of budget. It’s a great blend of experience to have and one that would see you fit into the “Unicorn” category in the eyes of some hiring managers.
Be a Business Brain
What we see time and time again, is Data Scientists who are employed to solve specific problems in the business, unbeknown to them (and their managers) that there are countless other problems they can solve too. The most successful commercial Data Scientists are the ones who can understand the rhythm of the business around them – how it works, why it isn’t working and taking ownership to solve the problem. You need to be able to proactively approach stakeholders within the business and confidently challenge them on the shortfalls of their department and how an application like Machine Learning can help the company be more successful. Engage yourself with the business. Have one eye on the project in front of you, but be able to identify where the next opportunity is coming from. Sell Machine Learning to everyone.
Become famous!
When we started Big Cloud, we were amazed at how online the Data Science community was. Compared to “old school” industries, it’s crazy how quickly you can make a name for yourself. We are constantly being asked by hiring managers to find them the best Kaggle Masters. Because of the accessibility of Kaggle, it has become a platform from which someone can gain notoriety very quickly. Another reason why managers like people who compete on Kaggle or partake in other extracurricular activities such as hackathons, is because it shows they have a genuine passion for the subject. How many hot shot lawyers finish a tough day in court, go home, log on and start solving cases in their spare time? How many Firemen go out looking for fires to put out when they’re not on watch? Data Science is an industry of discovery and people who are inquisitive and push themselves outside of work, in their own private research to better themselves, are being prioritised by more and more companies.
Look for the pool parties abroad
While there are many opportunities in the United States and the UK, as well as the rest of Western Europe, there are far more businesses in other parts of the world who are looking for Data Scientists. With lower tax brackets than the West, and a less saturated job market, you can expect to live very comfortably in say Bangkok or Kuala Lumpur for a fraction of the cost of London or San Francisco. If nothing else, it offers the opportunity to diversify your CV and solve problems that will benefit people in completely different parts of the world…how cool would that be! Just as important though, it’s also a chance to fulfill a desire of adventure.
Mo Money, Mo Problems
One of the biggest reasons we see offers rejected at final stage is because of a change in salary expectations. Sometimes it’s easy to increase your expectations at the last minute, particularly when the recruiting company have rolled out the red carpet and expedited their recruitment process from 4 weeks to 1 day, just to accommodate you. However, before you decide to hike your demands up at the last minute, consider your next move. It’s true, we see some candidates who not only price themselves out of the job, but sometimes the market entirely! It makes your job search that little bit trickier next time (who wants to earn less?), but it also means you’ll sometimes have to say goodbye to the businesses who are solving the most interesting problems. Strike while the iron is hot, but don’t get caught out in the abyss when equally skilled and cheaper rival applicants begin to emerge.
Get promoted
If there is an end point to your research days, a day when you’ve written your last line of code, perhaps a day when cleaning data is just too much of a pain , there is always a position upstairs. You will always find solace (and safety) in positions of management. Mentor and guide teams and become the parental figure. However, be prepared for the politics that can come along with this gig, as you will fight a daily battle with people in other areas of the business, who sometimes don’t have a clue what you do and why you’re telling them what they should be doing.
Start-up!
You don’t want to be replaced? Upstaged by a snotty nosed kid? Left to rot on the scrap heap? Simple, go into stealth mode and start up your own business! It seems like the most popular destination for most hardcore Machine Learning practitioners, who have a great idea and the balls to live it out. Build a proof of concept, showcase it and get a load of cash rich investors and don’t look back. How hard can it be?…
It’s critical that as Data Scientists who are always seeking to perfect and optimise your models and frameworks, you also need to take the same approach to who you are and what you’re offering to the world around you. When in the moment for here and now, it’s sometimes very easy to lose sight of what can and will be. One thing is for sure, with all the hype and attention Data Science is receiving in the press right now, this party is going to get a whole lot busier! Grab your shades, grip on tight and prepare for the swell!
image credit: Kajoaaa
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