Recruiting for the Data Sciences

The hiring manager tells you, “Another new hire isn’t meeting expectations.” New hires who don’t pan out not only foil the trust in the recruitment process but costs the business money. If you work for a small business, the cost of a poor hire could reach $8,000, and up to $240,000 for larger firms. These numbers do not include the costs of reduced productivity, damaged brand, decreased employee engagement, and increased management time spent on fixing under performance.

As a Recruiter, you work with the information you are given - what are the required skills and experience needed, what is the budget, where the person would be working and to whom they would report. You depend upon what the hiring manger tells you and have to prepare a job posting from this input. Without having a technical background, it is a challenge to discover why the previous hires weren't considered good hires.

But do you realize that there's an additional reason why your job is so hard?

Hiring managers' job descriptions are so technical, it's hard to feel confident in finding good candidates. Help.

Job descriptions for analytics specialists are ever evolving and can seem inaccessible. Consequently, the specs for the needed work become a bottle neck in your way of recruiting the right data or analytics candidate. The way the hiring manager wrote the job posting puts you in a tight spot. You know it should be modified, but without being a data scientist yourself, what can you change without attracting the wrong candidate or delaying the process. Also, you lose confidence in your ability to find the right person. Here are some tips to help you translate your hiring manager's requirements.

Yes, your company is having a hard time hiring qualified data scientists, and there are two reasons why.

When departments can't get the data analytics support they need, it can hinder progress for your company and risk your competitive edge. This lack of support can arise when people in other departments don’t know what types of data support they need. As a result, the recruiters who support them can’t recruit data scientists for the right roles or have to find qualified talent in a short time.

Do you struggle to find qualified candidates for data analytics positions? Are job descriptions and hiring requirements sometimes vague and other times overly technical?