Andre Schumacher is a data scientist at Simplaex, where he has spent roughly two years working on machine learning problems related to adtech: an environment defined by massive data volumes, adversarial dynamics, and the need for models that make fast, accurate decisions in real time.

His background before Simplaex spans the breadth of applied data science. He focused on recommender systems and search ranking in the online tourism and retail industry, worked as a data science consultant for several years across a wide range of fields, and built the kind of cross-industry pattern recognition that only varied client engagements can teach.

Andre’s academic grounding is equally solid. He holds a doctoral degree in computer science from Aalto University and a master’s degree from TU Darmstadt. His technical interests include classical machine learning problems, linear and convex optimization in operations research, and Bayesian modeling and statistics, a mix that informs both the rigor and the pragmatism he brings to production machine learning.