4 smart ways to maximize data science interns’ capabilities
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Your data science team is humming along nicely, and management decides it’s a good idea to assign interns to help your group. Are you excited yet?
If you’re anything like me, you have mixed feelings whenever interns enter the equation. Who couldn’t use more people to get things done, right? That said, how much disruption comes along with this brilliant idea? Well, that depends, but it’s definitely not zero.
Up until recently, data science teams have been reserved for the veterans — the brave, seasoned programmer/mathematicians who valiantly volunteered for the perilous role. However, the universities have quickly caught on, and they’re rapidly minting fresh new data scientists who are eager to explore their new profession. That’s where you come in to show them the ropes.
Your boss thinks it’s a good idea, and she’s the only one that matters. It’s up to you to make the most of the experience. Here are four key strategies for getting the most from your data science interns.
1: Consider generational differences
If your intern is just exiting college, chances are they fall into the Millennial generation. Like every generation, Millennials have been painted with broad strokes for quite some time. And although it’s dangerous to make assumptions based on general stereotypes, there are some common sense rules that can be applied to this group of young individuals.
The key to remember is that they’re much more in tune with social media than any other working generation. So, even though the incumbent communication culture of email caters well to the Gen Xers, your intern is about as interested in email as a cassette tape player. Millennials live in a world of texting and instant messaging, so to get their attention, Outlook is out and Lync is in.
2: Give them a real, unimportant job
It’s important to give interns a valuable experience with a minimal amount of disruption to the existing team. You do this by giving them a real, unimportant job. This is easily accomplished by mapping the feature set of your current analytic solution onto an opportunity matrix.
An opportunity matrix is a classic tool used in Six Sigma and other structured management methodologies that plots features on a double-axis chart containing business value and implementation complexity. The popular management term low hanging fruit, comes from the quadrant of this matrix that represents high business value and low implementation complexity. While your top data scientists work in this quadrant, give interns some features in the exact opposite quadrant: low business value and high implementation complexity. This gives them the full experience of being a data scientist, while minimizing the risk to your overall success.
3: Pair them with your top data scientists
With interns, you can limit your disruption, but you cannot eliminate it. As you may suspect, interns will need help — lots of it.
Data science seems academic; however, due to its multi-disciplinary nature, experience is the only way to become really effective. It won’t take long for your interns to get stuck, and as much as you need to get important work done, the right thing to do is to have your top data scientists help them out. That’s the whole idea of an intern program.
So, from a management perspective, just accept the reality that your throughput will drop in favor of helping the new kids out. This should be communicated upfront to your boss as a small price to pay for such a great idea of bringing interns into the mix.
4: Wish them luck and keep in touch
Alas, there will come a time when your intern must exit the lab and continue their journey elsewhere. Hopefully, you have taught them valuable lessons, and they’ll either proceed with a fruitful data science career — or not. Either way, you’ve provided a valuable service for this young mind, and you should feel good — but not terminal.
The data science community is a small but loyal crowd of passionate practitioners. The last thing you want to do at this point is lose touch. Leverage the Millennials’ affinity for social media and stay connected. You never know what value lies ahead for a future collaboration, but know it’s there.
Interns are necessary in some cases (especially when your boss mandates their presence), but they don’t need to be a necessary evil. In fact, they can put some exciting, unexpected features on your next analytic innovation if you play your cards right.
Open up your opportunity matrix, and reexamine those high-hanging porcupines you originally wrote off as being worthless. You never know; that porcupine might be the competitive feature that puts you over the top, and it would never happen without your disruptive, Millennial intern. Good luck.
Source: 4 smart ways to maximize data science interns’ capabilities
Via: Google Alert for Data Science