Are you tired of seeing the same batch of candidates from LinkedIn? Fear no more, with hireEZ IT/ Tech AI Sourcing, untapped talent is within reach!
hireEZ aggregates data from tech-specific platforms beyond LinkedIn including GitHub, Stack Overflow, and Kaggle. These platforms are not meant for traditional recruiting but instead are avenues for tech professionals to display their projects. That means hireEZ will capture all of those projects for your careful evaluation and help you focus on the best-fit candidates.
With 50+ Expertise (i.e. Machine Learning, Game Designer & Developer, Python Developer), 250+ Programming Languages, and varying involvement levels with community Coding Activities, you will be able to better target your search on the most qualified candidates for your open roles.
To get started, locate the IT/Tech sourcing feature via the "AI Sourcing” tab and then the “Tech” sourcing module on the left navigation bar.
You need to check the box first to enable hireEZ only to source candidates from the IT/Tech-related platforms. When you do so, you are still searching across hireEZ’s 45+ platforms, but with a focus on candidates who have online presences on GitHub, Stack Overflow, and Kaggle.
These are all platforms that encourage discussions and cooperation among technical engineers across the world:
-
GitHub: a cloud-based repository for open source code projects. Users can share their code or cooperate with other developers.
-
Stack Overflow: a question and answer site for programmers.
-
Kaggle: a platform specialized for data scientists.
Within these platforms, you are able to view the progress and contributions that your candidates have made in the field.
The Expertise section allows you to search for candidates based on their activities on the tech-specific platforms. You may type in keywords in the text bar and find related titles or fields from the drop-down menu.

You can also click on the View All Expertise button on the right and select from the list provided.

You may add more than one term here, but you are NOT able to input titles that are excluded from the list.
The Coding Activities and Impact Levels filter measures the candidate’s performance and contributions on GitHub, Kaggle, and Stack Overflow relative to other members of the sites. Candidates are categorized into the following tiers on hireEZ:
- No Activity Recorded: low activity or no data to be ranked.
- Somewhat Active: mid-level of activities.
- Active: frequent activities and good impact on the community.
- Very Active: the core contributors to the community.
Click on one or multiple tags to put in the search bar.
You may then move to other filters to refine your search. For instance, add information about the candidates’ Skills, Years of Experience, and Location, or select underrepresented groups that you want to target through our Diversity filter.
As in the case of other AI sourcing tasks, you can check out the Analytics page on the right and modify your search based on the information.
In addition to rankings already on GitHub, Kaggle, and Stack Overflow, hireEZ also takes into account a few other factors to determine the category best suited for each tech candidate.
The candidate’s overall rank is based on rankings for each programming language used and the numbers of activities, stars, followers, repositories, forks, watchers, and more. hireEZ analyzes all of these factors and makes the best judgment on the candidate’s involvement.
You can view the details of the candidate’s performance when opening the profile page.
Comments
0 comments
Please sign in to leave a comment.