by Armando Acosta
Being a data scientist is seen as one of the most lucrative and desirable jobs of the 21st Century. But the job comes with challenges for both companies and the data scientists they hire. For a recent article in CMS WiRE, Dell's Joanna Schloss took a deeper look at the shortage of data scientists and some of the possible solutions for success.
Among her suggestions:
1. Hiring from within may be the answer -The perfect data scientist may already be on your payroll. Internal candidates know your business, your culture, and your business goals. They can bring experiences an outside candidate simply cannot, which can provide a longer-term, more successful solution. However, Schloss also warns that only the right internal candidate should be chosen, and must receive your full support. Promoting from within simply because an external candidate cannot be found may cause you to second guess their insights, potentially negating the benefits you hoped to gain by having a data scientist on staff.
2. The right tools are as important as the right candidate - To be successful and provide proper insights and value, a data scientist must have access to the right tools. One such tool is self-service data technology. With the proper technology and tools, data scientists are better able to capitalize on your company’s big data investments, and provide the valuable business understanding you expect from them.
3. ROI isn't always immediate - Data analysis is an ongoing process, and result times vary. Patience and flexibility are important, but results are often well worth the wait.
Remembering Schloss' insights just may help your company avoid some of the hype and allow you to start reaping the rewards a data scientist can provide.