How our test assesses data science skills
Candidates will need to answer a range of questions that measure industry-specific technical skills where applicable (e.g. Microsoft Excel), soft skills (e.g. teamwork), aptitude (e.g. numerical reasoning) and relevant personality dimensions (e.g. detail orientation). The results present a holistic view of how well suited each candidate is for the job at hand, using a data-driven approach.
The format varies by type of question, including multiple-choice for aptitude and technical skills, situational judgement for soft skills and agreement on a Likert scale for the personality dimensions. This approach ensures candidates are being assessed in an accurate and fair manner, and that results reflect the true underlying qualities of each candidate.
The characteristics, abilities and knowledge necessary to be a data scientist were identified using the US Department of Labor's comprehensive O*NET database. O*NET is the leading source of occupational information that is constantly updated by collecting data from employees in specific job roles.
During the development process, test questions were rigorously analysed to maximise reliability and validity in line with industry best practices. They were created by our team of I/O psychologists and psychometricians – who collaborated with subject-matter-experts – and field-tested with a representative sample of job applicants who have varying experience, just like you might find in a talent pool.
Each test is reviewed by a panel of individuals representing diverse backgrounds to check for any sensitivity, fairness, face validity and accessibility issues. This ensures each candidate has a fair chance of demonstrating their true level of expertise.
Our data scientist test is monitored to ensure it is up-to-date and optimised for performance.