3 top mistakes hiring managers make with data scientists

Making a company’s first data science hire or working to quickly scale a data science team is a challenging and often frustrating undertaking. With the ever increasing demand for data scientists, more and more companies are confronted with their lack of tools and personnel equipped to handle complicated data problems.

According to Gartner, poor data analysis costs the average company $13 million every year. The massive losses associated with the rise of big data means that it’s boom times for aspiring data scientists. But for hiring managers who desperately need to find brilliant candidates the hiring process has become a rocky road littered with misleading resumes, poor demonstrated ability and capable candidates who lack real world business acumen.

Author: Tianhuili Michael Li


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