Overview
Charley Guillaume is the CTO of ifreq, a role he took up in January 2026. He is based in Namur.
Before joining ifreq he was technical lead at EarlyTracks from March 2024, and prior to that lead data scientist at HeartKinetics from October 2022 to February 2024. He was a machine learning engineer at We Invest Real Estate between April 2021 and September 2022, overlapping with a period as computer vision research engineer at Jitter from July 2020 to September 2022 and as lead software developer at ByVets SC from July 2020 to April 2021. He worked as a data scientist at DXC Technology from February 2019 to April 2021, and before that as a functional data integration analyst at Accenture Belgium, a business analyst at Alpha Networks SA and a CRM consultant at Business & Decision Belgium. Earlier roles include a C# development internship at RTL Belgium and successive positions at Proximus, where he worked as a student, then as a junior data warehouse analyst and datamart designer between 2014 and 2015.
He studied at the Haute Ecole de Namur, SUPINFO, the Louvain School of Management and the Université de Namur.
Career history
In the news
- Is data the new star of the pitch? According to a report published in September 2026 by Bpifrance and Les Meneurs, data, AI and digital platforms are becoming the main drivers of the sports economy, ahead of the traditional model built on TV rights and clubs. At IFREQ, we agree, with one condition: Data only shines when everyone can trust it and understand it. That's why we build a standardised test for football, scores validated by humans, and a pentagon any player can read. The stars are still on the pitch. Data just makes sure
- A machine measures. A human validates. That's one of the core principles behind every score at IFREQ. Our pipeline is fast and consistent. It analyses every exercise the same way, for every player, wherever they are. No bias, no bad day, no favourite. But a player's score can open doors: a trial, a detection match, a club's interest. When the stakes are that real, "the algorithm said so" isn't good enough. So before a score reaches a player, a human looks at it. 🤖 The machine brings scale and objectivity 🧑 The human brings context
- From 1 hour on a pitch to a player card: what happens in between? 🏟️ On the pitch: standardised exercises, recorded with the IFREQ app ☁️ In the cloud: videos and results uploaded securely ⚙️ In the pipeline: every exercise analysed and scored on the same scale ⬟ In the pentagon: off-ball, carry, defense, distribution, finishing ✅ In our checks: every score consistent and explainable 🃏 In the players hands: their card The player sees two moments: the effort and the result. Our job is everything in between, so that the result is
- Last Wednesday, 26 players took the pitch for an IFREQ detection match against Sporting de Charleroi. ⚽ None of them got there through connections, an agent or a highlight reel. They were selected because of their data. That's why we build IFREQ. Behind that selection are months of work from the whole tech team: 📲 An app that lets coaches test players on the pitch, anywhere ⚙️ A pipeline that turns every test into a reliable, comparable score ⬟ The pentagon, showing exactly where a player stands: off-ball, carry, defense,
- A score is useless if you don't understand it. At IFREQ, we're building the TOEFL for football: one standardised test that tells anyone, anywhere, where a player really stands. But a single number raises more questions than it answers. Why a 72 and not an 80? What's holding this player back? What should they work on next? That's why we built the pentagon. ⬟ Five dimensions: off-ball, carry, defense, distribution and finishing. One shape. At a glance, you see exactly where a player stands and why they got that score. And it works
- AI coding tools have changed what I look for in a hire. Technical skills still matter, but they're becoming easier to learn, augment and scale. What no tool can supply is how someone thinks, how they treat others, and whether they believe in where we're going. Over the past weeks I've reviewed a lot of applications for our open position at IFREQ. Many were strong on paper. Only a handful truly reflected the values we build on every day: Resilience, Positivity, Culture of excellence, Responsibility and Respect A strong CV tells me
- The team is growing! In this role, you will be owner of the backend, the pipelines, the scoring implementation, the ingestion and processing of thousands of videos. Do not hesitate to drop me an email charley[at]ifreq.io #Hiring #AI #ComputerVision #MachineLearning #DeepLearning #SportsTech #Football #Brussels
- A key role where you can grow and make the project grow. You'll own the architecture, the roadmap and bring iFreq to new highs. Send me a message if you are interested or have questions
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