Starcircle’s Eliza Molina was in a challenging position recently when a world-renowned brand needed highly specific and experienced talent, willing to work on-site. When traditional pipelines ran dry, Eliza created an alternative approach with great success, as she explains here.
When I joined Starcircle, I had never worked in talent acquisition: this whole world was new to me. A few weeks in, I was introduced to sourcing and the challenges it brings. Likely due to having a fresh perspective, I thought about finding talent outside the traditional routes such as LinkedIn and job boards.
After nearly a year at Starcircle, I started working on my own clients, rather than assisting my more experienced colleagues, and this ownership gave me more freedom to use different sourcing routes.
Through that ownership, I saw an opportunity to assist in the sourcing process of a Principal Audio Research Scientist role for an audio industry leader company. There were several requirements to be met by the candidates, including:
- A PhD
- Machine learning skills, and
- research experience focused around acoustics, spatial audio, and auditory perception.
For an added challenge, especially in modern recruitment, the role required lab work, meaning candidates either had to be onsite or willing to relocate.
In this case, due to the nature of the role, my mind went straight to places like Reddit and Discord – where tech specialists and industry leaders share insights and help fellow field enthusiasts.
When reviewing the options fed into Starcircle’s internal platform by our sourcing team, I saw a lot of incredible candidates that would have been ideal profiles for the majority of roles needed in audio software – the fact that none of these great candidates were exact enough for this position hammered home just how extremely unique this role was.
The more involved I got in the role, the more it showed itself to be an incredibly niche and difficult position to fill, ideal for me to test my theory. I decided then to start searching outside of traditional avenues, embracing Starcircle’s mission to uncover hidden talent and surface candidates beyond the normal pool.
TRIAL, ERROR AND BOOLEAN STRINGS
Putting my basic knowledge of boolean strings to test, I started my search with keywords on Reddit by using the site operator and different combinations. For example, some of the strings I tried were site:reddit.com “music” “acoustics” “DSP” machine learning, site:reddit.com “acoustics” “spatial audio” plugin, site:reddit.com “acoustics” “machine learning” perception.
This search provided me with a few subreddits related to the field of acoustics, which included conversations about machine learning, DSP, and spatial audio. In one of those, I hit my first bullseye.
This candidate matched all of the requirements and brought even more skills to the table. Sharing the profile with the client’s in-house recruitment team and finding out the candidate was already in the interview process assured me that I was on the right track.
Now, fully confident in my process, I went on to find the absolute goldmine – Twitter. While I did find several good profiles on GitHub, Reddit, and Discord, Twitter was the gift that kept on giving. There, I found 27 strong candidates from a total of 36 within a week.
From there, I began to send personalized outreach, where I mentioned the candidates’ previous publications or projects, as well as specific skills that were very relevant to the role. This approach encompassed complimenting their academic and professional journey, and any accomplishments that stood out (e.g.: patents, awards, TED talks).
In addition to these candidates, I also decided to target very experienced professionals and tenured professors who though might not be interested in going for the position, could have a pool of qualified candidates in their network (including former alumni, peers, etc) to recommend.
At this point, my response and interest rates were considerably higher when compared to those from our general outreach. With this encouragement, I personalized my outreach even more and went on to ask candidates who were not interested for referrals as well.
Overall, this alternative approach resulted in a total of 106 suitable profiles from my own sourcing — plus 8 referrals. From these, there were 40 responses to my outreach, 18 of which were interested in learning more about the position and booked prescreen calls. In the end, a wider sourcing strategy — as well as a more personalized outreach — rendered 11 qualified, interested, and relevant candidates (QIRs) between the months of October and November. In comparison, general outreach from May to September had provided us with 11 interested candidates, resulting in 5 QIRs.
This ‘experiment’ proved to be extremely successful. After reviewing 100 profiles that had been submitted, our client’s recruiters highlighted 18 suitable profiles that mostly fit all requirements, from which 8 were candidates I had uncovered from alternative sources. One of those candidates is currently in their interview process. I wish them well!
The Molina Method
- Always try to keep a fresh perspective on sourcing;
- Don’t restrict yourself to the same searching avenues each time;
- A niche role needs a niche approach;
- Target a network not just perfect candidates – a professor might recommend a former student for example; and
- Make evidence-based decisions.