Seventy percent of US company recruiters used virtual technology for at least 50% of candidate interviews and onboarding, according to Monster's 2021 survey. Remote interviews are also being embraced by applicants as COVID-19 continues to disrupt traditional hiring processes. In this article, we will discuss how to set up remote Python coding challenges for interviews that benefit both the interviewer and the candidate.
There are five steps to conducting Python coding challenges for candidate interviews. First, setting up the test in a remote environment with clear parameters; second, proctoring the test; third, automating results; fourth, setting different levels of difficulty according to role functions; and lastly, providing feedback to the candidate. Let’s take a look at each step below.
The first thing to consider is how the remote Python coding challenge will be administered. There are several options available, such as using a web application or a dedicated platform with pre-installed packages for testing. It’s ideal to provide candidates with any additional packages needed to complete the challenge. Web applications available online may not always suit specific criteria unless they are custom-built for a company’s coding test. However, a dedicated platform can accommodate necessary technical requirements for an in-depth assessment.
Once the application or testing platform is set up, you will need to define clear evaluation criteria for the challenge. This sets an objective standard for scoring and eliminates bias. Next, consider setting a time limit for the test. The time limit should be based on the test difficulty.
The next step is to set up a proctoring system for online monitoring of the test. Make sure to inform the candidate of proctoring guidelines such as video monitoring or copy-paste tracking. Lastly, schedule a follow-up discussion with the candidate after the interview to wrap things up. It is also a nice touch to let candidates add their completed tests and results to their portfolios.
Fraud detection and prevention helps ensure the right candidate gets the job. That being said, proper proctoring also respects applicants’ boundaries and promotes a stress-free environment for taking the test. Here are several practices for proctoring Python coding challenges for interviews:
Automating results saves time and speeds up the hiring process. Automatic assessment tools can be set up to compare an applicant’s code output with a test case result to determine a pass-or-fail score. A dedicated testing platform can also evaluate a candidate’s coding and execution time, code quality, and usage of memory. Advanced tools can automatically rank candidates compared to other applicants based on scores.
Best-in-class technical testing platforms can be used to benchmark a company’s internal IT team and compare their performance to applicants’ outputs. This helps HR and recruiters more accurately fill skill gaps.
If possible, automated results should be given in a format accessible to both technical and non-technical recruiters.
Coding challenges should offer different levels of difficulty depending on the role for which you’re interviewing. Below are some ideas for Python coding challenges based on expertise level:
Once the Python coding challenge is complete, interviewers may proceed to discuss the challenge with the candidate. This is a good time to ask about the candidate's approach to the coding test and probe their thought process about the task. Candidates who value learning and self-improvement will appreciate feedback on their work whether or not they are selected for the job.
If possible, assist the candidate in adding the completed test to their portfolio. This extra step builds positive sentiment around your company’s hiring process and attracts more talent in return.
Filtered’s end-to-end hiring platform excels in coding challenges with task simulation, live video, and technical interviewing. It offers best-in-class simulation environments for code, front-end, SQL, data science, and DevOps challenges so you can observe candidates' expertise and performance in job-specific scenarios. All these features constitute a holistic approach to skill-based hiring for technical talent such as Python coding challenges for interviews.
What's more, Filtered is ready for integration with existing applicant tracking system platforms that other hiring services may not support. Compared to others, only Filtered supports integration with Beeline, SAP Fieldglass, and Zapier ATS platforms.
Filtered is a leader in skill-based, data-driven recruiting technology. Our end-to-end hiring platform enables you to focus on skills, spend time reviewing the most qualified candidates, and streamline workflows. We’ll help you humanize hiring while also applying data-driven techniques to select the right candidates. To get started, contact our team today or register for a FREE demo.
