The unicorn is having a moment in the spotlight. I’m not just talking about recent myriad of new unicorn-themed merchandise at your favorite retailer, I’m also referring to the data science unicorns that are so coveted in today’s workforce. This rare data science unicorn is a perfect blend of statistics and math, data engineering and data visualization skills – all bundled with an inquiring mind and thirst for data exploration.
There’s a reason these highly skilled, multi-talented individuals are dubbed ‘unicorns’ – the unicorn is rare and finding someone with depth in all these skills sets is not easy. (If they have experience solving corporate world business problems they become even more valuable as they have proven they can make the leap from academia.) Many unicorns are lured into joining corporate behemoths, such as Google with their endless perks and stockpiles of brand recognition. Others choose to join smaller start-ups with big potential. So how does a mid-sized D.C. consulting firm compete?
Truth is, at Excella we realized that even if we find and retain a few data science unicorns, there just aren’t enough of them in the marketplace. We needed a unicorn alternative to sustainably grow our data science group, so we turned to our proven cross functional team model to see if this was viable approach. Instead of having one person do it all, we decided to spread the load across the team and staff multiple people with complimentary skill sets.
- Data scientists use math and stats skills to explore the available data and understand patterns (and anomalies). They then identify optimal techniques to solve the given business problem.
- Data engineers review the source data and focus on the data quality (then work to remedy issues found). Their goal is to build automated data pipelines that move required data from source to target with pre-emptive error-handling and alerts, plus the necessary transformations.
- Data viz specialists are experts on intuitive presentation formats and the multiple self-service options users choose to access their data. Their focus is getting the right data into the right hands, so decisions can be made and actions taken.
This trio of skill sets works collaboratively to deliver a robust and sustainable outcome; the team supports each other and learns from each other as well.
Yes, we have three people instead of one. Here’s why it works for us:
- Work gets done faster due to more bandwidth available.
- Risk is reduced because the work does not rely on one super human individual.
- Three sets of experiences and expertise generates more diverse ideas, which proves helpful when solving complex problems.
- Team members get to focus on more of the work they want to specialize in.
- Increase in awareness of different tools and techniques with opportunities to learn from others.
Together Everyone Achieves More.