While data scientist candidates can be interviewed and assessed using traditional methods, it can take a long time before an accurate portrayal of the candidate’s caliber is formed. In-person interviews go through many steps, such as scheduling, initial meeting, test setup, technical interview, and scoring to assess each applicant. Virtual testing with skills-based hiring techniques is the best way to evaluate the technical skills for data scientist candidates.
The most qualified data scientists will accept the best positions. Interviews allow candidates to showcase their skills and make a great impression. Companies also use them to showcase their value to the candidates. With a shortage of data scientists and a plethora of available positions, data scientists can select the job that fits their needs best as well. Interviewers must conduct assessments to evaluate the technical skills for data scientists and select the best candidates, but also to allow candidates to assess and select your company. These four expert tips can help recruiters train for their best evaluations!
Time is essential for assessing and securing data science talent. A take-home technical interview narrows the candidate pool to qualified applicants compared to a manual hiring process. In addition:
Moreover, best-in-class technical interviewing incorporates candidate authentication and fraud detection features to ensure the validity of results.
Here are a few guidelines on evaluating data scientists' technical skills using a take-home interview:
Data science sits at the intersection of different fields, including mathematics, machine learning, programming, data manipulation, and more. When learning how to evaluate technical skills for data scientists, your evaluations must cover the core skills listed below.
Testing core skills are critical because many are attracted by the glamor and promising salaries of a data scientist’s job. However, not everyone who has visualized data using charts, graphs, etc., has adequate training and background in data science. Virtual whiteboards with diagram building and integrated development environments (IDEs) can help accurately assess these skills. Testing candidates for core skills immediately reveals who is qualified for the job and is likely to succeed.
If there’s one thing you should take away from this guide, it is to align the technical interview experience with the job's actual duties. Don’t take the easy way out and use generic or multiple-choice tests to evaluate your candidate’s technical skills.
A better strategy is to leverage technical hiring platforms using real-life data science projects such as:
The best scenario is to model a data science test based on the nature of the company’s business. For example, reviewing engineers can assign retail-related challenges such as inventory database management or logistics planning using predictive analytics if a retail company is looking for data scientists.
After the test, it’s best practice to give candidates a chance to explain their approach to solving the challenge. Take-home interviews are best paired with video-recorded explanations so reviewing engineers and senior data scientists can follow candidates’ thought processes throughout the evaluation.
At this point, you can begin determining culture fit. Observe how candidates planned their solutions, any errors they made, and the steps they took to fix mistakes.
For live post-test interviews, reviewing engineers can use this portion to explore further the candidates’ job knowledge and grasp of their subject. Some questions to guide the conversation include:
In summary, a take-home interview is the best way to evaluate the technical skills of data scientists. Reviewing engineers should test core skills to filter out unqualified applicants early in the hiring process. Data science tests are best patterned onto real-world scenarios for accurate skill assessment. Lastly, reviewing engineers should explore candidates' thought processes through a post-test interview or a recorded explanation.
Filtered offers ready-to-go data science assessments using Jupyter, Python-3, R, SAS, Java-8, and more to help you align technical interviews with the position you’re hiring for. We have developed a unique scoring rubric that assesses error numbers and compares applicant outputs to benchmark test cases. Our tests have fraud detection values to ensure the integrity of results. Furthermore, Filtered’s technical hiring platform enables live video so you can evaluate the technical skills of data scientist candidates in detail.
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.