Data scientists are in high demand. IBM predicts that job demand in the data science industry will grow 28% by the year 2020. It makes perfect sense – as the amount of data available continues to grow, our reliance on data to make smart marketing and business decisions grows too. That means we’re going to need an army of superior data professionals to keep up with future demand. Unfortunately, data science is still growing in popularity and experts are anticipating a large shortfall in professionals versus the demand for them. Knowing this, you’ve got to have a plan ready to attract talent and keep them happy in your most important data roles.
Here are five ways to keep your data scientist happy.
1. Show them support and give them direction. According to a Forbes survey, 27% of data scientists don’t feel they are adequately supported by their management teams. This is an easy one to overcome. Every employee, no matter their role within the organization, or how smart and capable you think them to be, should be given a clear objective and support to achieve that objective.
2. Hire for the job. If you’re looking for an analyst, hire an analyst. If you’re looking for someone to model, hire someone who can build models. Don’t hire a predictive analytics specialist and expect them to spend the majority of their time cleaning data. Make sure the skills you hire for will be used – not all data-focused jobs are the same.
3. Invest in tools. Give your employees the best possible chance at success by investing in the proper tools for them to complete their work in a timely and efficient manner. Excel spreadsheets are not those tools! Do research, or let them tell you what they need, to ensure they are provided an opportunity to add great value to your business.
4. Ask for insights. These employees know your data better than anyone else. Ask for their opinions and investigate their work by asking questions. Showing your respect and attention for their work will keep them happier longer. Don’t treat them like the dusty computer in the corner!
5. Outsource the dirty work. This is a big one – and a place some companies aren’t comfortable going. 80% of data science work is cleaning data – that only leaves 20% of time for analysis and the creation of useful and actionable insights. There are so many resources available in today’s marketplace that this issue doesn’t have to be an issue any longer.
If this last item is plaguing your data science team, I’m happy to say that B2E has a resource that can save you time and money doing the dirty work of cleaning data. MotusBase Analytic Engine can take data from multiple sources, clean it and provide it back to your team in a ready-to-go format. Save yourself a few data scientists, especially since we all know they are in high demand, and let us do the dirty work for you. Contact us today to learn more about MotusBase Analytic Engine.