3 changes that will strengthen your data science team

Data science is a hot topic, and data scientists are the hot commodity. Google the phrase and there are a zillion results, many of which reference the most disruptive startups and innovative corporations. It’s all data science all the time these days.

But before you create a data science team, it’s important to recognize that hiring data scientists and creating a data science team isn’t a magic elixir. Hiring data scientists isn’t the answer by itself. Using data science to move your business forward is about building a culture that uses the scientific method when using data to understand and address problems.

[aditude-amp id="flyingcarpet" targeting='{"env":"staging","page_type":"article","post_id":2011672,"post_type":"guest","post_chan":"none","tags":null,"ai":false,"category":"none","all_categories":"big-data,entrepreneur,","session":"C"}']

While there is no one size fits all to building and strengthening your data science team, there are things you can consider to improve the likelihood of success in your company.

1. Don’t get caught up on specific skills

When hiring for an open position on your data team, it’s easy to make a list of the skills you know will get the job done and look for someone that fits in that box. But as with most things in life, taking little risk will give you little reward.

Hiring the same person with the same skills over and over again will often produce the same results. In some roles at your company, that’s exactly what you want. That’s not what you’re want when it comes to data science — you want people who will bring a variety of perspectives and insights to the job.

It’s important to fill your next data-focused hire with someone who can think critically about a problem, regardless of whether they have experience working with the specific tools you use or have a direct background in your industry. This will allow for more candidates, opening your company up to the advantages that can come from people with a variety of perspectives.

At my company, Rover.com, we’ve found success hiring out of academia. Do physicists know what a dog owner is looking for in a dog walker? Maybe not, but they are able to look objectively at a problem, analyze data, and draw logical conclusions. Our data science team has many finds across academia, including a nuclear engineer, an imaging specialist, and a biologist who specialized in mushroom and insect interaction. This method of hiring will lead you to attack problems from multiple perspectives and, in turn, provide better reception in the market.

2. Stop separating analysts from business managers

As you’re building your team, it’s easy to operate with a business unit on one side and a data and analysis team on the other, but separating those two roles doesn’t generate the collaborative insight that can yield extraordinary results. As you can imagine, it leads to slower conclusions when problems arise and many employees not understanding the true goals of the business.

Ideally, it’s valuable — especially in a rapidly growing company or startup — to hire a data team that can see projects through to the end. If they’re able to both do the analysis and apply solutions to the business, you’ll find much more comprehensive decisions and quicker results.

3. Never put your data in a corner

Every company should be thinking about the future of business and data — and the symbiotic relationship they have. To take full advantage of the benefits data can provide, it’s important to create a culture where you don’t have to be a “data scientist” to appreciate the powerful insights data can provide.

[aditude-amp id="medium1" targeting='{"env":"staging","page_type":"article","post_id":2011672,"post_type":"guest","post_chan":"none","tags":null,"ai":false,"category":"none","all_categories":"big-data,entrepreneur,","session":"C"}']

All our employees, from engineering to marketing to customer service, are trained and encouraged to generate their own reporting, as opposed to waiting on a request to get fulfilled by someone on our analytics team. Each employee can build reports specific to their function in the company from our data warehouse. When we enable processes this way, we are empowering employees to take control of their own data and make strategic changes based on the findings.

In today’s world, we are all tasked to keep up, no matter our position. People who are proactive and gather information on their own will move faster in their careers and will help your company get an edge up on competition.

Scott Porad is CTO of Rover.com.