Summary
Babs Olaniyi is a data scientist with nine years of experience building applied machine learning systems that turn complex health and commercial data into actionable decisions. Currently at Causal Foundry in Barcelona, she focuses on data products for healthcare financing, provider performance, and scalable reinforcement-learning approaches to improve patient outcomes. Her background spans pricing and demand-forecasting systems at ZF Group, digital health personalization at benshi.ai, and customer analytics for growth-stage businesses, giving her a rare blend of econometrics, product analytics, and production-ready modeling. Trained in econometrics and quantitative economics across European universities, she prioritizes models and metrics that are actually used in policy and operations and enjoys mentoring early-career professionals. An understated strength is her track record of translating archival and messy real-world datasets into robust pipelines and decision tools that non-technical stakeholders can trust.
9 years of coding experience
5 years of employment as a software developer
Master of Science - MS Econometrics and Quantitative Economics, Master of Science - MS Econometrics and Quantitative Economics at Universitat Autònoma de Barcelona
Master of Science - MS Economics, Master of Science - MS Economics at Bielefeld University
Master of Science - MS Econometrics and Quantitative Economics, Master of Science - MS Econometrics and Quantitative Economics at University of Paris I: Panthéon-Sorbonne
Bachelor of Science - BS Mathematics and Statistics, Bachelor of Science - BS Mathematics and Statistics at KWARA STATE UNIVERSITY, MALETE
Spanish, English