Recruiting for the Data Sciences

Not long after you learn that the company is not meeting current expectations, a hiring manager tells you that a data visualizer you'd hired quit. When you ask why, the response is not unexpected, "because there were not enough career advancement opportunities."

You understand that retaining top talent is vital to meeting your organization’s business goals. However, you also know that the data science labor pool is small. Improving retention has to be addressed.

Data professionals, young and old, whether data visualizers, data wranglers, business analysts or other related roles, are likely to pursue new opportunities for these top two reasons: compensation and lack of career growth.

Hiring managers keep telling you that it is taking too long on average to fill data science positions.
In response, you want to create a pool of pre-qualified candidates so that you have a list of data professionals you can hire quickly for short-term or long term projects.