Data Scientist Coding Assessment: Achieving a More Efficient Hiring Process

June 28, 2022
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Data scientist coding assessments help engineers to hire better and faster through skill-based testing, real-world challenges, and automated scoring.

Expertise in data science is hard to pin down given its multidisciplinary nature. Candidate assessment is therefore difficult and time-consuming, tempting many companies to skip testing and rely on credentials for hiring decisions. In this article, we're going to look at how an online data scientist coding assessment is a better and more efficient way to hire data scientists. 

Data Scientist Coding Assessment

Data science sits at the intersection of several fields, including mathematics, analytics, domain expertise, machine learning, statistics, and more. Coming up with a coding test that touches on all these subjects is quite a challenge, even for the most knowledgeable engineer. Not to mention that tests take up a lot of time on both sides — candidates spend hours to complete a project, and engineers spend even more time assessing individual candidate output. Some employers take the easy way out and ask for references, hoping that others have done their homework on the candidate. 

A better alternative to both these scenarios is to take advantage of online, remote data scientist coding assessments. Its benefits include skill-based testing, streamlined assessments, and automated scoring for a faster hiring process. Let’s take a closer look. 

Performance Over Pedigree

Technical hiring platforms use performance as the main criteria for candidate scoring. With online data science assessments, engineers can use objective scores to qualify candidates for the role instead of relying on negotiable factors like education, certain training backgrounds, appearance, and other personality traits to guide their decision.

Best-in-class platforms have advanced features that obscure personal characteristics, so the technical interview is focused on skill. Advanced platforms also employ fraud safeguards to ensure the validity of test results among applicants. 

Data scientist coding assessments benefit interviewers and applicants, who get a taste of on-the-job duties during the testing process and not on their first day on the job. This real-world testing scenario helps reduce early resignations due to job misalignment and saves resources from being wasted on the hiring process. 

Streamlined Assessments

Data science tests can be understandably data-heavy and require special tools/environments. Technical hiring platforms take care of test requirements (ex. Jupyter Notebooks environment), so candidates don’t have to worry about setup, installation, and other preliminary steps. In addition, engineers can assign tests that mimic real-world projects such as: 

  • Model selection
  • Parameter tuning
  • Data visualization
  • Metric selection
  • Data cleaning
  • Feature engineering

Furthermore, best-in-class technical hiring platforms are designed to handle multiple candidates taking data scientist coding assessments simultaneously. This characteristic allows companies to invite more applicants to take the test for the data science position.

Automated Scoring 

Once the test is over, engineers and senior tech team members are often required to evaluate candidates’ output. This manual scoring process can take a heavy toll on engineers who are pulled away from their main duties to interview and score dozens of random applicants.

In contrast, technical hiring platforms quickly filter out unfit applicants based on test results, so engineers only need to spend time with the final shortlist of the best candidates. 

Online data scientist coding assessments are automatically scored based on predetermined criteria and ranked on a leaderboard. Best-in-class platforms use test cases for output comparison and factor in error count, time-to-complete, and other criteria in scoring. Engineers can also opt to listen to video explanations to understand candidates’ approaches to the challenge better. With all these capabilities, the hiring process for a data scientist can be drastically cut down. 

In summary, online and remote data science coding assessments hosted on a secure testing platform save significant time on both sides. Candidates can jump into the test without worrying about tools, technical environment, or scheduling. Engineers can skip unnecessary sessions of lengthy interviews with unfit applicants and only spend time with shortlisted candidates. Lastly, online data science coding assessment promotes hiring based on performance over pedigree and ensures better culture fit and longer retention.

Hire The Right Person For The Role With Filtered.ai Tests

Filtered provides engineers with the right data scientist coding assessment for the job. Choose from our ready-made tests, including questions in Jupyter, Python-3, R, SAS, Java-8, and more. Our team has developed a unique scoring rubric that counts error numbers and compares applicant outputs to benchmark test cases. Our platform also enables video interviews, live whiteboards, and video recordings for technical interviews. With Filtered, you can save time and align technical interviews with the position you’re hiring for.
Engineers enjoy these benefits using Filtered’s dedicated platform:

● 3X Faster Time-to-Hire

● 50% Less Time Interviewing

● 2X Better Interview-to-Hire Ratio

Choose the right data scientist coding assessment for your job opening with Filtered today.

Filtered is a leader in skill-based, data-driven recruiting technology. Our end-to-end technical hiring platform enables you to spend time reviewing only the most qualified candidates, putting skills and aptitude at the forefront of your decisions. We’ll help you automate hiring while applying objective, data-driven techniques to consistently and confidently select the right candidates. To get started, contact our team today or register for a FREE demo.