On October 2nd, Entrepreneur Magazine featured another article written by Data Incubator founder Michael Li. The article can be found where it was originally posted here.
These days, there’s a lot being said about big data and the value that comes from properly utilizing it. I’ve written previously about the importance of having a data science team. The next goal is to figure out how to keep those data scientists happy.
At The Data Incubator, we’ve spoken to hundreds of companies looking to hire data scientists from our training program. They’ve ranged from large corporations like Capital One and eBay to smaller, nimbler outfits like Betterment, Upstart, and Mashable; and all have been eager for suggestions on how to retain their data scientists.
Even without the capital provided by a larger corporation, there are plenty of ways — most of them free — for scrappy entrepreneurs to keep their data scientists engaged and on board. Here are three tips:
1. Give your data scientist a purpose.
It’s important for data scientists to understand how the work they do fits in with the broader mission of the business. To help make them feel like valued members of the team, have them spend time with business or product units. This will provide them context to better understand the problems they are facing and, in turn, will strengthen their analyses.
Feeling valued will also lead them to make better products and deliver better services to your customers. The more connected they feel, the better their work will be.
Data scientists, like many technical employees, get motivated by solving challenging problems. So, find intellectually stimulating new questions for them to work on or ask them to come up with their own. Engage them by encouraging them to work on compelling data sets. Allow them to work with your engineering staff to automate their repetitive weekly tasks. These things will help keep them connected to the company and keep them mentally sharp.
2. Help your data scientist foster a sense of ownership.
Entrepreneurs are often strapped for cash, so it makes sense to allow your data scientist to utilize his or her favorite open-source tools. Data scientists don’t exist in a vacuum; they’re part of a larger network of peers collaborating in an open-source movement. Encouraging them to contribute to open-source projects, and giving them the time to do so, gives them a greater sense of ownership and a broader purpose: contributing to the open-source community.
If open source alternatives are not available, buy or build your own tools. Seek the data scientists’ input for the procurement or purchasing process. In the same way that a chef gets frustrated working with someone else’s dull knives, data scientists will become equally frustrated if forced to use the wrong tools for the job. Involving them in the decision-making process will increase their sense of ownership and avoid jeopardizing their morale and desire to stay with your company.
Recognize the accomplishments of your data scientists and make sure you give them credit for their hard work. Good data scientists can take terabytes of data from a number of sources and synthesize that data into a single, succinct graph. This can be challenging work, even if they make it look easy, and this work is often overlooked.
Letting your data scientists present their findings to management (and publicly thanking them when they do so) will help them feel connected to the company’s broader mission. And, after all, no one is more familiar with the analysis than the data scientist who performed it.
3. Provide your data scientists with the support they need.
As an entrepreneur, you may not have a team of engineers set up to assist your data scientist. Even so, recognize that data science and engineering go hand in hand, and do what you can to provide enough engineering support for your data scientist to get the job done. If the data clusters are slow, it will be difficult for your data scientists to iterate quickly, and the result will be a loss of motivation and creativity.
They may also want software tooling support so that they are not writing MapReduce from scratch. Make sure the tools at hand are appropriate for the job in terms of both type and speed.
There are also always new skills for data scientists to learn that could help them better leverage data to the company’s benefit. When possible, invest in their education. If you can afford to do so, pay for additional training classes to keep them on the cutting edge. As a less expensive option, cover lunch so they can hold seminars to teach one another new tricks, or provide space for hosting meetups with academics and data scientists from other companies.
Doing these things will show that your company really does care about the data scientists and the work they do. Plus, you’ll be building up your team’s skill set in the process.
Entrepreneurs are notoriously scrappy and capable of coming up with creative solutions to the challenges they face. Utilizing some of these techniques should enable you to keep your data scientists engaged and on board. And the more engaged they are, the happier they’ll be to stick with you and provide quality work.
Editor’s Note: The Data Incubator is a data science education company. We offer a free eight-week Fellowship helping candidates with PhDs and masters degrees enter data science careers. Companies can hire talented data scientists or enroll employees in our data science corporate training.
