Data Scientist Ashleigh Bynum explains how data teams should identify talent and collaborate in ways that leverage past experience
By Ashleigh Bynum
When many people think of technology departments, they picture fairly traditional limitations in terms of backgrounds: coding, information technology, and development. But, our team at SVG understands this is no longer the reality in the tech industry.
I’ve noticed companies are recognizing that technical skills can be taught, unlike soft-skills such as problem-solving and creative thinking. Tech companies are shifting their hiring goals and widening their net, increasingly hiring less-traditional employees with varying backgrounds and experiences. This philosophy not only expands the hiring pool, it inspires further growth and advancement.
Backgrounds ranging from liberal arts to history can bring new skills to technical roles, such as expertise in project management, analysis, and research. Diversifying your data science team allows for new perspectives for solving problems — and it is critical for innovation.
Expanding possibilities through creativity
At Spring Venture Group, our data science team is filled with people from dissimilar backgrounds: my experience is in business; some coworkers have proficiency in physics or economics; others have received PhDs; truly it’s a widely diverse group.
Some think that data science is purely logical. But for us in the profession, we know it expands far beyond into areas like creativity, empathy, and communication. When you have unique educations and experiences on your data team, you’re capable of really opening the possibilities by allowing for a greater variety of solutions.
For example, certain industries use specific algorithms in data science. Having a group of people from various industries allows for an expanded knowledge pool — where different algorithms can be applied to specific problems, which may have not be available (or even known) without the broad experience set.
Promoting collaboration across disciplines
We work on systems and solutions that help seniors all across the nation make better health care decisions; because no two seniors are alike, it’s imperative that we understand the diversity in our client demographics. Having the ability to collaborate across our own personal experiences helps us understand our users better and provide them a superior, more well-rounded experience.
Each data scientist that works on a problem brings their unique skill set and background to the situation. Collaborating and combining the unique tools and knowledge we’ve gathered allows us to solve problems in new ways.
Inspiring personal and professional growth
This variety is also important in order to spark employee growth. I work with a group of truly brilliant people and I am constantly learning from them every single day. It’s not always just about the success of the business itself; diversity of experience is just as important for the development of each individual.
In a career like data science, where it’s ambiguous and open, it’s imperative that companies continue to instill and inspire a passion for growth. Becoming stagnant and repetitive is a fatal flaw for data science teams; growth is what continually inspires innovation and success.
And when you’re surrounded by people who think differently than you — ones who have unique and ingenious ideas and solutions — it’s nearly impossible to avoid personal and professional progress.
In a field where we are challenged to responsibly use and protect customer data, having more capabilities in the room helps produce the best possible outcome. It would be a disservice to both employees and customers to limit the backgrounds on a data science team.
Having a breadth of experience in your data science team encourages creativity, collaboration, and personal growth. Management should emphasize the importance of recruiting from various backgrounds and experiences in order to truly enact innovation and change in the company.