Olaf

When Olaf tells the story of his scientific path, it all begins in Yaoundé, Cameroon. His most vivid memory isn’t of a blackboard or an inspiring teacher, but of his grandmother running her small roadside doughnut stall. “She had never been to school, yet she did all her calculations in her head without ever making mistakes. That fascinated me.” With a child’s eyes, this intuitive mastery of numbers opened a door: mathematics is a powerful, universal language.

Naturally, Olaf chose the scientific track in high school, followed by a bachelor’s and a master’s degree in mathematics in Yaoundé. An international partnership then enabled him to join a master’s program in applied statistics at the École Polytechnique of Cameroon, before pursuing a PhD in France at Télécom ParisTech.

His thesis topic? Detecting malicious attacks in Orange networks using time-series analysis. “It was already data science, even if the term didn’t really exist yet.” Olaf also discovered a decisive mentor — his thesis supervisor — who encouraged him to deepen his use of data and AI as decision-support tools. “Without funding at first, he even hosted me.’ That encounter shaped my entire career.”

After completing his PhD, Olaf knew he didn’t want to stay in academic research. His goal: apply mathematics to the real world. But he also wanted to teach and make complex concepts accessible. “I thought: what better than consulting to learn how to simplify? Consultants know how to present complex things in a way that makes people want to understand.” This formative period helped him find his professional posture: making data understandable, interpreting it, convincing.

After consulting, he joined the CEA (French Alternative Energies and Atomic Energy Commission) to work on the aging of electric vehicle batteries, a very first step toward environmental challenges. He later moved on to Adomik, a start‑up specializing in intelligent advertising campaign analysis, followed by SNCF CONNECT, Stellantis, and even an expatriate experience in Madagascar and Mauritius, where he led the data teams of an African telecom group. There, he contributed to the development of mobile money and nano‑credit solutions for unbanked populations: “Thanks to AI, it is now possible to grant and manage very small loans that can be easily repaid via a mobile phone. This promotes financial inclusion.” Everywhere, Olaf seeks the same balance: robust models, immediate usefulness, tools to improve everyday life. “I love solving real-world problems with data and AI. Every algorithm can have a very real impact.”

In 2023, he joined SUEZ to coordinate data scientists and data engineers within Digital Solutions. His mission: design, deploy, and maintain the algorithms used across the Group. Applications are numerous and deeply linked to environmental impacts: leak detection in water networks through customer consumption modelling; computer vision in sorting centers to better classify recyclable materials; automatic detection of non-conforming (mattresses, gas cylinders) or recoverable items (wood, plastics, cardboard) in waste-to-energy plants to prevent accidents, reduce costly stoppages, and improve operational performance; energy optimization of wastewater treatment plants… “My job is to use data to help make better decisions. And for SUEZ, every good decision means saving water, energy, resources, or reducing waste.” 

Today, Olaf manages a team of about twenty people and leads a community of nearly 80 data scientists worldwide. Transmission is key to his management style: “I’m by their side to help them grow. I still code with junior team members — and I learn from people younger than me too.”

Curious and passionate about learning, Curious and passionate about learning, Olaf occasionally teaches data science at both a university and an engineering school in France and abroad, and he also spends time supporting his children who, like him, love mathematics. The next generation seems assured: his 11-year-old son competes in Île-de-France chess championships, and he can easily imagine his 13-year-old daughter pursuing a scientific career. Diversity is also an important issue for him: his team includes nearly one-third women, a proportion he aims to increase.

Every day, Olaf is guided by a deep conviction: artificial intelligence is not meant to replace humans, but to assist them. “AI isn’t here to make people disappear. It’s here to help them work more efficiently.”

From doughnuts sold on a roadside in Yaoundé to algorithms detecting leaks in Paris water networks, the thread remains intact. For Olaf, numbers have always had meaning — and today, that meaning is measured in liters of water preserved, tons of waste better sorted, and energy saved. A mathematician serving the real world, convinced that well‑used data can truly change things.