About

Arash Rai is a highly motivated and skilled Machine Learning Engineer with a Bachelor's degree in Software Engineering from the University of Waterloo. He is passionate about machine learning, data science, and infrastructure and has gained significant experience in these areas during his career. Currently, Arash is working at Stripe as a Machine Learning Engineer, where he is focused on fighting credit card fraud using ML. He is part of the Radar team, which is responsible for detecting online fraud using ML. Arash is involved in hyperparameter tuning for fraud detection models using Bayesian Optimization, resulting in a 6% increase in recall. He also generates and prepares data for ML experiments using Scalding and Spark jobs, runs experiments in Jupyter Notebooks, and writes reports on findings. Additionally, he analyzes and improves the stability of Stripe's framework for continuously training, evaluating, and productionizing models. Prior to joining Stripe, Arash worked as a Software Engineering Intern at Citadel, where he developed tools for trading and quantitative research purposes on the Equities Technology team. He also worked as a Machine Learning Intern at Stripe, where he gained experience in hyperparameter tuning, data preparation, and model stability analysis. Arash's education history includes a Bachelor's degree in Software Engineering from the University of Waterloo and a High School degree from Abbotsford Traditional Secondary School. He has gained experience in various technologies, including ML, Data Science, infra, Research Scientist, Jupyter, Hyperparameter, and Spark. With 2.78 years of relevant experience, Arash is a highly skilled and motivated Machine Learning Engineer who is passionate about using ML to solve real-world problems. He is a quick learner, a team player, and has a proven track record of delivering high-quality work.