Data Scientists work really hard to upskill their technical competencies. A rapidly changing technology landscape demands a continuous ramp up of skills like mastering a new programming language like R, Python, Java or something else, exploring new machine learning frameworks and libraries like TensorFlow or Keras, understanding cutting-edge algorithms like Deep Convolutional Networks and K-Means to name a few.
Had they lived in Dr.Frankenstein’s world, where scientists worked hard in their labs, cut-off from the rest of the world, this should have sufficed. But in the real world, data scientists use data and work with people to solve real-world problems for people. They need to learn something more, that forms a bridge between their ideas/hypotheses and the rest of the world. Something that’s more of an art than a skill these days. We’re talking about soft-skills for data scientists.
Today we’ll enjoy a conversation between a father and son, as we learn some critical soft-skills for data scientists necessary to make it big in the data science world.
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One chilly evening, Tommy is sitting with his dad on their grassy backyard with the radio on, humming along to their favourite tunes.
Tommy, gazing up at the sky for a while, asks his dad, “Dad, what are clouds made of?”
Dad takes a sip of beer and replies, “Mostly servers, son. And tonnes of data.”
Still gazing up, Tommy takes a deep breath, pondering about what his dad just said.
Tommy: Tell me something, what’s the most important thing you’ve learned in your career as a Data Scientist?
Dad smiles: I’m glad you asked, son. I’m going to share something important with you. Something I have learned over all these years crunching and munching data. I want you to keep this to yourself and remember it for as long as you can, okay?
Tommy: Yes dad.
Dad: Atta boy!
Okay, the first thing you gotta do if you want to be successful, is you gotta be curious! Data is everywhere and it can tell you a lot. But if you’re not curious to explore data and tackle it from every angle, you will remain mediocre at best. Have an open mind – look at things through a kaleidoscope and challenge assumptions and presumptions. Innovation is the key to making the cut as a data scientist.
Tommy nods his head approvingly. Dad, satisfied that Tommy is following along, continues.
Dad: One of the most important skills a data scientist should possess is a great business acumen. Now, I know you must be wondering why one would need business acumen when all they’re doing is gathering a heap of data and making sense of it.
Tommy looks straight-faced at his dad.
Dad: Well, a data scientist needs to know the business like the back of their hand because unless they do, they won’t understand what the business’ strengths and weaknesses are and how data can contribute towards boosting its success. They need to understand where the business fits into the industry and what it needs to do to remain competitive.
Dad’s last statement is rewarded by an energetic, affirmative nod from Tommy. Smiling, dad’s quite pleased with the response.
Dad: Communication is next on the list. Without a clever tongue, a data scientist will find himself going nowhere in the tech world. Gone are the days when technical knowledge was all that was needed to sustain. A data scientist’s job is to help a business make critical, data-driven decisions. Of what use is it to the non-technical marketing or sales teams, if the data scientist can’t communicate his/her insights in a clear and effective way? A data scientist must also be a good listener to truly understand what the problem is to come up with the right solution.
Tommy leans back in his chair, looking up at the sky again, thinking how he would communicate insights effectively.
Dad continues: Very closely associated with communication, is the ability to present well, or as a data scientist would put it – tell tales that inspire action. Now a data scientist might have to put forward their findings before an entire board of directors, who will be extremely eager to know why they need to take a particular decision and how it will benefit the organization. Here, clear articulation, a knack for storytelling and strong convincing skills are all important for the data scientist to get the message across in the best way.
Tommy quips: Like the way you convince mom to do the dishes every evening?
Dad playfully punches Tommy: Hahaha, you little rascal!
Tommy: Are there any more skills a data scientist needs to possess to excel at what they do?
Dad: Indeed, there are! True data science is a research activity, where problems with unclear or unobvious solutions get solved. There are times when even the nature of the problem isn’t clear. A data scientist should be skilled at performing their own independent research – snooping around for information or data, gathering it and preparing it for further analysis. Many organisations look for people with strong research capabilities, before they recruit them.
Tommy: What about you? Would you recruit someone without a research background?
Dad: Well, personally no. But that doesn’t mean I would only hire someone if they were a PhD. Even an MSc would do, if they were able to justify their research project, and convince me that they’re capable of performing independent research. I wouldn’t hesitate to take them on board.
Here’s where I want to share one of the most important skills I’ve learned in all my years. Any guesses on what it might be?
Tommy: Hiring?
Dad: Ummmmm… I’ll give this one to you ‘cos it’s pretty close. The actual answer is, of course, a much broader term – ‘management’. It encompasses everything from hiring the right candidates for your team to practically doing everything that a person handling a team does.
Tommy: And what’s that?
Dad: Well, as a senior data scientist, one would be expected to handle a team of lesser experienced data scientists, managing, mentoring and helping them achieve their goals. It’s a very important skill to hone, as you climb up the ladder. Some learn it through experience, others learn it by taking management courses. Either way, this skill is important for one to succeed in a senior role.
And, that’s about all I have for now. I hope at least some of this benefits you, as you step into your first job tomorrow.
Tommy smiles: Yeah dad, it’s great to have someone in the same line of work to look up to when I’m just starting out my career. I’m glad we had this conversation.
Holding up an empty can, he says, “I’m out, toss me another beer, please.”[/box]
Soft Skills for Data Scientists – A quick Recap
In addition to keeping yourself technically relevant, to succeed as a data scientist you need to
- Be curious: Explore data from different angles, question the granted – assumptions & presumptions.
- Have strong business acumen: Know your customer, know your business, know your market.
- Communicate effectively: Speak the language of your audience, listen carefully to understand the problem you want to solve.
- Master the art of presenting well: Tell stories that inspire action, get your message across through a combination of data storytelling, negotiation and persuasion skills
- Be a problem solver: Do your independent research, get your hands dirty and dive deep for answers.
- Develop your management capabilities: Manage, mentor and help other data scientists reach their full potential.
