Recruiting, Staffing, & Interviewing

Our consulting services are often more cost effective than hiring an in-house analyst. However, we understand that some companies have requirements to bring on staff instead of using external firms. Boxplot offers recruiting and staffing services for data roles.

The Goal

Your ultimate goal is to find the best person for a given job. This of course involves more than just the technical piece – cultural fit, communication skills, domain knowledge, and other factors will come into play. But in our experience, most hiring managers struggle the most with finding someone who possesses the right technical skills. It’s costly to make the wrong choice – finding a poor fit often results in:

High turnover cost (SHRM average is $15,000 per employee)

Wasted time and money by the candidate as well as the HR team

Poor team morale

#1. Start with a Clear and Accurate Job Post

Too often, we see job descriptions that don’t actually match what the candidate will be expected to do once they are in the role. Here are some common mistakes:

  • You expect the candidate to be able to use a particular application like Microsoft Excel, Tableau, or Power BI very well but don’t specify this explicitly (including detailed information about level of knowledge) in the job posting.
  • You list too many applications in the job posting to try to “cover all bases” instead of what is actually needed for the work, which deters qualified candidates.
  • Using vague or high-level descriptions like “proficient in SQL”.

#2. Find the right candidates

We use the best in class applications and software to find the right candidates for the job. We know what to look for in LinkedIn profiles, resumes, and cover letters when choosing candidates. We can do the work of finding ava

#3. Interviewing Data Talent

There are three key metrics by which to judge data talent: domain knowledge. communication skills, and technical know-how.

Although it can be difficult to judge technical ability if your organization doesn’t already have an in-house data team to evaluate technical skills, the other two don’t require any data competence- in fact, organizations tend to underestimate the importance of the latter two metrics.

Domain Knowledge

In terms of domain knowledge, simply get an impression of how well the applicant understands the industry in which your organization operates. Without this, it will be very difficult for the applicant to be optimally effective working with data pertinent to your industry.

Communication Skills

Communication skills are especially important if you’re hiring data talent for the first time, but always important nonetheless; if the applicant can’t effectively communicate the highly-technical results of their analysis into terms that anyone can understand, they quite flatly will not be valuable to your organization.

Technical Skills

And as for technical skills, Boxplot is happy to help you evaluate your candidates’ abilities. Our own knowledge base spans all areas of data engineering, data analytics, statistics, and data science, and hence we’ll make sure to set you up with an expert from our team who is in the best position to assess applicants’ skill sets.

#4. Ask the right questions in technical interviews

Unfortunately, this is something we hear all of the time. Especially if your organization doesn’t have in-house data professionals currently who can vet applicants, it can be very challenging to ensure the data talent you’re hiring and staffing is competent in the skills you need for a given role. The technical interviews are crucial. Here’s an example of how these usually go wrong:

Hiring Manager: “Tell me about your experience with SQL.”
Candidate: “I’m very proficient in SQL, I used it in a few previous roles and have experience with a few different SQL programs.”

This is not enough information to accurately determine the true skill level of the candidate. Many candidate unfortunately will inflate their abilities and when they aren’t pressed for specifics or details, won’t provide a complete picture of their skills. Here is an example of how the same question would differ in a Boxplot interview:

Boxplot Recruiter: “Have you performed JOINs in SQL before?”
Candidate: “Yes, I have experience with JOINs.”
Boxplot Recruiter: “How would you handle the following JOIN question?” [Shows candidate example business scenario]
Candidate: “I would use a LEFT join from that so I retain all information from the sales table.”
Boxplot Recruiter: “Great, and what about CASE statements, have you used those?”
Candidate: “No, I haven’t, in my previous role I only did SELECT statements with filtering.”

#5. Post-Placement Support Option

If your organization doesn’t have a lot of other technical people on staff, don’t worry! We offer the option of supporting the candidate post-placement as well. We give the candidate access to our community of data scientists and analysts so they can ask any specific questions they need to perform better at their job. It’s as if they are part of a regular data team!

They can ask questions like:

  • How do I perform this particular task in Python?
  • Can someone review my Excel formula to see why it’s not working?
  • I’m having trouble with a specific task in Tableau – anyone know how to do this before I sink a lot of time into research?

Candidates can be on your payroll or Boxplot’s payroll.

Case Study

Boxplot worked with a leading HR Recruiting Firm whose specialty is placing HR professionals of all levels across all industries. Data is relatively new to the HR field – the term “People Analytics” is booming now as more and more companies recognize the value in understanding their HR data and marrying it with other data sources within the company like finance. Even though this HR Recruiting Firm had decades of experience placing HR roles, the more technical data HR roles were new to them and they wanted to enlist the help of the Subject Matter Experts at Boxplot for the recruiting process. HR Recruiting Firm’s client had no one available to complete a technical interview for the candidate, even though they were a large firm.

We found qualified candidate options for them and interviewed those candidates, which included a rigorous and detailed technical interview. We then presented the candidates to the HR Recruiting Firm, who presented them to their client. The client was happy with the options, and chose one of the candidates for placement. Boxplot continued to support this candidate, where she had access to our instant messaging platform and could ask questions of the Boxplot team at any time regarding her current role.

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