Jacob Nogas

Jacob Nogas is a Data Scientist currently at Lyft, focusing on A/B testing and causal inference to drive profit and manage substantial spending. Prior experience includes a similar role at Amazon, where Jacob developed metrics for A/B testing that significantly impacted revenue generation. Previous positions at Thomson Reuters involved assessing clustering algorithms for legal tech and conducting research on NLP model robustness. Jacob's academic background includes an MSc in Computer Science from the University of Toronto and participation in the Simon Initiative LearnLab Summer School at Carnegie Mellon University, with earlier studies in Statistics, Physics, and Philosophy.