The People team helps to advance Q-Centrix’s mission and vision, in part by stewarding a vibrant culture where every team member feels a strong sense of belonging and community. As a fast-growing and leading clinical data management company in the healthcare industry, our Talent Specialists make a huge impact at Q-Centrix by attracting, sourcing and recruiting culturally additive talent to the company.
We are looking for a healthcare recruiter to support our Talent team in our recruiting efforts. This full cycle recruiting role will be reporting to the Sr. Manager, People Analytics and Talent Optimization in Chicago. Although we prefer this contract recruiter to be in Chicago, we are open to remote recruiters as well.
- Leverage strong healthcare recruiting knowledge in order to recruit and fill current clinical data abstractor openings, while quickly building a candidate pipeline for future roles.
- Partner with the Talent Team Lead in order to understand current recruiting goals and drive recruiting efforts based on high priority needs.
- Communicate Q-Centrix’s Employee Value Proposition (EVP) effectively in order to attract healthcare industry professionals
- Utilize LinkedIn Recruiter, Lever, Indeed and other tools in order to source and process candidates.
- Share effective sourcing and recruiting strategies with the Talent team as best practice when it comes to Recruiting team learning and collaboration.
- Provide process improvement recommendations as necessary.
- 4+ years of experience in healthcare industry recruiting, sourcing registered nurses, clinical leaders, and/or allied health professionals.
- Strong sourcing experience with a strategic approach on how to recruit in a passive candidate market.
- Experience using Applicant Tracking Systems. Lever experience is a plus!
- Excellent ability to communicate clearly and effectively with candidates and internal teams.
- Ability to develop strong relationships with candidates and prospects, as well as with teammates and hiring teams.
- Experience recruiting for clinical data abstractors