Aris Budi Wibowo
A data professional with over five years of experience in the fintech, e-commerce, and banking industries. He has led projects using Python to enhance customer behavior models, improve product adoption, and increase operational efficiency, delivering measurable business outcomes.
Previously, Aris worked with major banks and one of the biggest e-commerce platforms in Indonesia, where he developed predictive models for cross-selling and operational improvements, driving gains in customer engagement and process optimization. He is passionate about leveraging Python and machine learning to transform data into actionable insights that drive innovation and growth.
Session
Discover powerful alternatives to A/B testing for measuring experiment impact using causal inference techniques. This talk will demonstrate how we can leverage the matching process methods, such as propensity score matching to reduce bias when comparing groups, providing reliable metrics even when traditional A/B testing isn't feasible. Learn practical applications, and new approaches, and gain actionable insights to broaden your data analysis toolkit and effectively measure the impact of your features or products.