Talent Spotlight — Eóin Gaynard (No. 3 — 2025)

Welcome to Talent Spotlight — where every month, we shine a light on standout talent professionals and the real stories shaping our industry.

Hey Eóin, tell us a bit about yourself. Who are you, where are you, and what keeps you busy these days?

I'm Eóin (pronounced "owen"), a French-Irish professional from Paris, soaking up Berlin's vibe for nearly 11 years now! These days, I'm working to bridge my fresh Data Science, Machine Learning and AI certification with my 11 years in Talent Acquisition. I've built recruiting teams, worked as a 360 recruiter, and filled roles across Europe, the Middle-East and Africa in tech, automotive, and chemical manufacturing sectors.

Your Story

An "aha" moment:

My "aha" moment came while leading a Tech Recruiting Team. We were confidently preparing for huge hiring projects based on client forecasts when suddenly — the calls started coming in. First one client announced a hiring freeze, then another went quiet. Our forecasts were completely wrong.

Sitting back in my chair, I thought about all the incredible Data Science candidates I'd interviewed who specialized in prediction — hospital occupancy rates, financial downturns, pedestrian behavior for self-driving cars. And it hit me (AHA!): why weren't we using these skills in Talent Acquisition? Could we have anticipated this downturn?

That realization drove me to learn these skills myself. After leaving my Team Lead role, I taught myself coding and completed LeWagon's AI & Data Science bootcamp.

Something from a completely different field that helped your talent work:

I actually started my career as a consultant in IT Security, spending 4 years improving trading systems to avoid fraud at financial institutions. While I was TERRIBLE at that job, being embedded in IT teams became a huge advantage when I switched to recruiting — I could genuinely relate to tech candidates and understand why they squirmed under formal HR interviews. It showed me candidate experience must be tailored to get the best out of the talented people we're speaking to.

Talent Talk

The most unconventional thing you've done in recruiting that worked really well:

Back in my Paris days, I sometimes ditched the formal office interview setup for candidates who seemed like they might not shine in that environment. ☕ Instead, I'd invite them to meet at a café nearby for a cappuccino. Also works with a lunch or even an after-work beer.

A trick or productivity hack that makes life easier:

My go-to interviewing trick is super simple but effective: I dedicate the first few minutes to genuine small talk. If the candidate on the phone is being a little distant, I won't hesitate to use those few minutes to tell them about myself — how my weekend was, what my morning was like.

As recruiters, we forget how nerve-wracking interviews are for candidates. By creating a safe space upfront, I give them time to "arrive" into the conversation and show them they can be open with me. This approach has saved countless interviews from awkward robot-mode responses.

One thing about TA you've completely changed your mind about:

(CV) gaps can be explained, and a solid recruiter should be able to discuss those and help the candidate explain their journey so it can be properly comprehended by — and even sold to — the Hiring Partners.

💥 Now those are often the people I'm most excited to talk to!

Community Connection

• Nataliia Reznichenko of Futurepath — joined my team in 2022 and instantly kicked us into high gear. She's incredibly data-driven and always hunting for ways to optimize, but also one of the most genuinely empathetic recruiters I've ever worked with.

• Jonathan Giordano (now at Kao Corporation) — back when I was in the chemical industry, he completely transformed my understanding of HR reporting. Those chats planted the seed that eventually led me to dive into Data Science years later.

My burning question:

How are you actually using predictive analytics in your recruiting strategy and staffing plan? And are you ensuring your current processes collect the right data to enable these solutions when the time comes?