So You Want to Be a Data Scientist
Author:CSC Town Hall
Companies that thrive in the next decade will be those that value a data-driven workforce. In recent years, we've seen the swift rise of the data scientist, the data engineer and many other roles in data science. But what exactly does a career in data science involve? What do these professionals do all day? Our experts offer insights into the future of data science and give practical suggestions on how to succeed.
- Jin Zhang, Senior Director of Analytics, CA Technologies
- Jerry Overton, head of advanced analytics research at CSC’s ResearchNetwork and CSC Distinguished Engineer
- Jeff Caruso, Senior Managing Editor, CSC
So You Want to Be a Data Scientist
Companies that thrive in the next decade will be those that value a data-driven workforce. In recent years, we've seen the swift rise of the data scientist, the data engineer and many other roles in data science.
Jin Zhang, senior director of Analytics at CA Technologies says the variety of data careers has expanded dramatically. “There are many ways to work in data science today. We have data scientists who work with data to develop the best models possible. Data engineers are good at moving large volumes of data and interconnecting them. Then there are data visualization experts. The list goes on to cover the entire lifecycle of the data journey, and it offers plenty of opportunities,” Zhang says.
Diversity is an important element and one which needs to be stressed. Jerry Overton, head of advanced analytics research at CSC’s ResearchNetwork and CSC Distinguished Engineer, says this goes beyond the usual visible characteristics. For example, a greater range of thinking styles would benefit the entire field.
“My perception is that the field is dominated by people who think mathematically and deductively. There’s nothing wrong with that, but there are other ways of thinking — metaphorically, inductively — I personally am a computational thinker,” Overton says. “It’s important to stress that you don’t have to think one way to be good at this job or get to insights.”
Zhang says the discipline is already delivering great business value across industries and business functions. “Data-driven marketing gives us a much clearer picture of the customer mindset so we can deliver the right campaign or promotion in real time, right when the customer walks by your store. Data-driven product management can help you determine among all the different paths a product could take, which is the most desired,” she says.
Despite the breadth and depth of opportunity, the number of people entering the field falls well short of demand. Overton says one of the biggest obstacles is how the field is portrayed.
“The description is left up to people in the field, and we are often notoriously bad at communicating how cool our jobs really are,” Overton says. “I’ve felt my heart rate jump when I’ve discovered a new connection in a set of data and realize I’m the first person in the company to have ever seen it.”
Zhang says the best way to get started in the field is to begin exactly where you are. “If you start with a mathematic or statistical background, try to connect the numbers and models you have to business needs. If you’re a software architect, look for ways to inject data science into your approach. Start with a small plug-in to see if the outcome of that could be incorporated.”
Overton agrees. “You can take a certain set of classes then apply for a certain job and that’s fine. But if you look for ways to apply elements of data science, you’ll move closer to that field until you realize you’re doing more data science than anything else,” he says.
“Everyone wins. Your company gets a sought-after resource, your business unit wins because you’re bringing new skills to the table. And you win because you’ve entered a new career.”