Capabilities VS Skills Based Assessments For Hiring Data Scientists Part 1

Part 1 covers creating job descriptions and screening resumes. The change in focus from skills to capabilities helps me hire faster and improve employee outcomes. Here's how I do it.

What’s the difference between a skill and a capability? Programming is a skill. Knowledge of statistics or model architectures are skills. Capabilities are the ability to apply a skill or skills to create a business outcome or work product.

When we assess Data Science candidates, we must gauge their ability to create a business outcome. However, most interview processes stop at skills. The baked in assumption is, if the candidate has all the skills, they will be able to create a range of impacts and work products.

In reality, we know that’s not true. Interview processes have some awareness of this disconnect. Many create a hybrid approach to compensate. Already lengthy interview processes can become ridiculous. Add capabilities based rounds to skills rounds and it becomes a 4+ round process. Most qualified candidates have already been hired by a more streamlined process or they decide to abandon the process midway through.

What Capabilities Does The Candidate Need?