Filter

Narrowing down vast applicant pools can feel like finding a needle in a haystack. You allocate so much time searching and sifting, you end up speeding through interviews, hiring, and onboarding.

Particularly for frontline jobs, applications quickly pile up. Manual filtering by recruiters is not only a low-value process, it returns inconsistent and noisy decisions.

Customized filtering & tech

StellarEmploy’s approach to filtering leverages data-driven automation with dynamic, unbiased tech.

• What our clients gain: timely, unbiased applicants ready to interview.

• How we present ready-to-interview applicants: dynamic, easy-to-use client dashboards.

IN THE BACKGROUND: AUTOMATION & FEEDBACK

The pathway to automated filtering and technological feedback loops starts with data wrangling.

Client HR data, particularly characteristics of workers who stay and thrive, are crucial. We also analyze current applicants through our research-based job preferences survey tool, resumes, and other application tools. 

Our hiring algorithms are trained on client-specific data and complemented by industry datasets as needed. But we know data and data trends aren’t stagnant. StellarEmploy’s machine-learning algorithms improve through automated feedback loops from the subsequent applicant, interview, hiring, and retention metrics.