Data Scientists continue to be the toughest to find professionals because of the diverse skill sets needed to be a top performer in data science. In the simplest of terms, a Data Scientist takes what the data analysts and data engineers generate and makes business decisions based on both data analytics (hard skills) and business metrics (soft skills). We crunched the data on recent job postings to see what companies require and prefer when hiring Data Scientists.
Hard Skills are much easier to define and recruit for since they are common skills that are typically required by most companies and the keywords are searchable.
The Soft Skills are the most dynamic and tough to define when it comes to Data Scientists since these are on the business metrics side. These skills are not easily recognized when reviewing resumes and profiles so it takes a talented professional to highlight these skills in their resume and most importantly, show examples and ROI results. It's then up to the Recruiters and Talent Acquisitions Specialists to recognize these skills and further research throughout the sourcing process.
Here are a few Soft Skills that are becoming more common in Data Scientist job requirements.
If you are a Data Scientist and want to be recognized as being at the top of the data science class, don't forget to highlight and build your soft skills.