Evaluating Candidates for Your Data Teams Approaches to Hiring: 1. The right job description: 3. The interview and selection process: 4. Conclusion

So you know what you need in a good data scientist, but do you know how to evaluate these fundamental skills? What resources are available to support your decision-making process?

With the ever-changing landscape of data, analytics and digital transformation efforts, knowing how to identify good candidates is critical. 

Approaches to Hiring:

For experienced hiring managers selecting candidates can feel routine. But challenges persist in ensuring that incoming talent is the right fit for your team or organization. Do they truly have the right skill set? How likely are they to grow into the role — or even future leadership positions? 

These are especially large complexities for technical or analytics roles. 

Here are some ways to ensure you get the right fit on your team.

1. The right job description: 

It’s an obvious place to start, but an often overlooked step. To ensure you’re getting the right candidates, it’s important for them to know what role they’re applying for. Some things to consider:

  • Describe (in general terms if necessary), your team’s mission. A simple statement that reads “we support the CXO in executing sales related data analytics” will be enough to indicate to candidates what you’re looking to achieve and how you fit in the organization. 
  • Be specific (but don’t be catch-all) on the tools and infrastructure the candidate needs in the near-term. Oftentimes, job descriptions include an alphabet soup of tools, programming languages, databases and cloud technologies. This can work against you, as the candidate you need may select out of the process for fear of not having the right experience. 
  • Provide a sense of what “success” looks like. A statement to the effect of “In this role, you’ll be asked to develop interactive visualizations using [insert the tools or technologies] and dashboards for the leadership team to support sales insights, that are timely, relevant and actionable” will give candidates an understanding of what you’re expecting as an outcome of hiring them into the role. 

2. Pre-screening and evaluations:

The hiring process can be time-consuming and at times, exhausting. Having candidates take your time when they don’t have the correct hard or soft-skills you need can add to the frustration.

There are tools available that can help you identify a more appropriate slate of candidates for your data or analytics needs. 

  • Skill evaluations and assessments: After an initial narrowing of the candidate pool through your applicant tracking system, you may still be left with a large number of candidates who are technically eligible for the role. As an initial step, you may consider leveraging technical skill assessments to provide an objective view into who has the skill sets you need. 
    Chisel Analytics skill assessments may be a good resource, providing objective testing at a low cost across statistics, business analytics, data interpretation, data science, data engineering, machine learning and AI, or dashboard and reporting development. 
  • Certifications: Similar to assessments, candidates certifications can be a good barometer of who has invested in their skill set in particular areas in a way that will make them more successful in the role. Consider certifications from leading business intelligence providers, such as SAS, Oracle, Amazon Web Services, or data science programs.
    Of course, certifications are best paired with academic or professional experiences relevant to the role and your firm. This is where your Human Resources or staffing partner can support you. 
  • Human resources and staffing support: Staffing and human resources support is critical throughout the process. For firms looking to move fast, or looking to build a team to support a particular initiative, a staffing firm focused on analytics and data science/services can be critical. For instance, Chisel Analytics can help you find talent quickly to tackle new or existing initiatives. This can include permanent or contract-based roles. 

3. The interview and selection process:

The effectiveness of interviews has come into question in recent years. Many times, unconscious bias or day-to-day interruptions can play a role in how your or your team perceive a candidate. For example, coming out of a tense meeting can influence your perception of a candidate.

For this reason, most of  the work for selection should be done before the interview process, and this element of the decision should be mostly about the candidates fit and soft skills. There are a few things to consider when interviewing for data-focused roles.

  • Hands on experiences: Interviews are a great opportunity to assess the candidates hands-on experiences directly. While the assessments will give you a good sense for their technical capabilities, you may use this time with them to directly ask how they would tackle certain problems or use technology in the role — from your perspective.
  • Logic and real-world responses: Particularly for more analytically-focused roles, logic or case-based questions relevant to your team and the role are a good way for you to assess how a candidate would respond to a typically problem. For example, giving a candidate a real-world data set from your team and having them define an outcome or relay how they would approach the problem can be an effective way to evaluate their skills.
  • Communication and other “soft” skills: Soft skills, while critical, are often influenced by external factors. Still, communication and interpersonal interactions with others are important to ensuring the candidate will be successful. Lean on your HR or staffing partner, other members of your team, or key partners to help you make this assessment so it’s not a subjective perspective.



4. Conclusion

Evaluating and selecting new candidates for your analytics or data science team can be challenging and time-consuming. And there can be a lot at stake. 

But, there are key things you can do to narrow the candidate pool and focus your time and efforts on finding new candidates that are the best fit for your needs. 

At Chisel Analytics, we specialize in helping you build a pipeline of analytics and data-focused talent, so you can more easily narrow your candidate pool and move forward with the right individuals for temporary or longer-term needs. Our assessment process provides you a resource that can help you objectively evaluate the skills of your candidate pool. 

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