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.
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.
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.
This article was originally published on www.venturebeat.com and can be viewed in full


Archive
- October 2024(44)
- September 2024(94)
- August 2024(100)
- July 2024(99)
- June 2024(126)
- May 2024(155)
- April 2024(123)
- March 2024(112)
- February 2024(109)
- January 2024(95)
- December 2023(56)
- November 2023(86)
- October 2023(97)
- September 2023(89)
- August 2023(101)
- July 2023(104)
- June 2023(113)
- May 2023(103)
- April 2023(93)
- March 2023(129)
- February 2023(77)
- January 2023(91)
- December 2022(90)
- November 2022(125)
- October 2022(117)
- September 2022(137)
- August 2022(119)
- July 2022(99)
- June 2022(128)
- May 2022(112)
- April 2022(108)
- March 2022(121)
- February 2022(93)
- January 2022(110)
- December 2021(92)
- November 2021(107)
- October 2021(101)
- September 2021(81)
- August 2021(74)
- July 2021(78)
- June 2021(92)
- May 2021(67)
- April 2021(79)
- March 2021(79)
- February 2021(58)
- January 2021(55)
- December 2020(56)
- November 2020(59)
- October 2020(78)
- September 2020(72)
- August 2020(64)
- July 2020(71)
- June 2020(74)
- May 2020(50)
- April 2020(71)
- March 2020(71)
- February 2020(58)
- January 2020(62)
- December 2019(57)
- November 2019(64)
- October 2019(25)
- September 2019(24)
- August 2019(14)
- July 2019(23)
- June 2019(54)
- May 2019(82)
- April 2019(76)
- March 2019(71)
- February 2019(67)
- January 2019(75)
- December 2018(44)
- November 2018(47)
- October 2018(74)
- September 2018(54)
- August 2018(61)
- July 2018(72)
- June 2018(62)
- May 2018(62)
- April 2018(73)
- March 2018(76)
- February 2018(8)
- January 2018(7)
- December 2017(6)
- November 2017(8)
- October 2017(3)
- September 2017(4)
- August 2017(4)
- July 2017(2)
- June 2017(5)
- May 2017(6)
- April 2017(11)
- March 2017(8)
- February 2017(16)
- January 2017(10)
- December 2016(12)
- November 2016(20)
- October 2016(7)
- September 2016(102)
- August 2016(168)
- July 2016(141)
- June 2016(149)
- May 2016(117)
- April 2016(59)
- March 2016(85)
- February 2016(153)
- December 2015(150)