January 28, 2025

Vetted job seekers for tech recruiters

Co-Founder of DevScanr

Co-Founder of DevScanr

Head start in your recruitment process

Leveraging a passive candidate database enables recruiters to identify many potential matches. The number of engaged and qualified candidates, however, is often limited by the following issues:

Database quality. Even a per-quarter refresh is not fast enough for hiring. Key points, like current positions, can be outdated and contain errors.
Low response rate. The person you will contact is unlikely to look for a job at the moment.
Unreliable skill claims. Owners of “perfect resumes” are increasingly failing tech interview rounds.

Vetted Job Seekers is a new product of DevScanr, aimed to resolve these challenges by identifying and vetting tech professionals who are open to new opportunities.

Here’s how it works. Our algorithms find developers who are preparing to change jobs (or are already searching). Their profiles are analyzed, ranked and the best seekers are pre-selected. It all happens automatically and, at the next step, our topic experts verify and approve the results.

Curated lists of candidates are finally published to our Telegram channel. Recruiters can subscribe to threads per desired location(s) and receive a consistent flow of vetted tech prospects. If you’re regularly looking for software engineers, web/game/mobile developers, data/ML engineers, analysts/scientists, devops/secops/dataops, architects, QA and testers, etc. – you will benefit from the new product.

How talent lists are created and why you can trust them

Improving a database quality with algorithms

Many of our blog posts cover this topic. The next documents, in particular, describe how DevScanr inferences complement resumes and outperform any scraped profile dataset:

Fixing low response rates with Hireability Signals

In 2024 our team created an algorithm to discover signals of hireability. The algorithm finds developers about to change jobs – sometimes months before they share a corresponding status on LinkedIn. The quality of such signals is verified and consistent, please check our published research for details.

The current accuracy of hireability prediction reaches 80%. In other words – 4 out of 5 profiles, forecasted to change a job by this algorithm, actually do that. It’s likely even more, because for the remaining 20% we simply don’t know whether they changed their minds or failed interviews and reconsidered.

Vetted Job Seekers lists include hireability metrics for each posted profile.

Fixing unreliable skill claims with Vetting

The vetting process for the new product is multi-faceted.

The qualification process starts with an automatic analysis of public GitHub repositories, contributions, activities, social metrics, ratings, etc. by dedicated ML-based algorithms. The goal is to extract valuable insights of dev. capabilities and preferences. Unlike resumes, such open data is difficult to forge due to omnipresent timestamps.

Crowd-assessment is another facet of our vetting approach. Earned stars and followers are heavily taken into account in ranking.

To make sure no mistakes are made on the previous stages, all profiles undergo manual reviews by human experts – before they are posted in a channel. We also collect information that is not typically present on GitHub.

Besides, DevScanr has a certification program for developers. All participants of this program are contacted and interviewed by our team. Such profiles are as truthful as you can get, and you will see them via our Telegram channel as well.

Vetted Job Seekers lists include only vetted profiles.