Sijie Li is a Senior Data Scientist at Bill.com, where he leverages his extensive expertise in machine learning and statistical modeling to tackle complex challenges in payment fraud detection and customer onboarding. With a strong foundation in Python and advanced tools like H2O.ai and XGBoost,...
Sijie Li is a Senior Data Scientist at Bill.com, where he leverages his extensive expertise in machine learning and statistical modeling to tackle complex challenges in payment fraud detection and customer onboarding. With a strong foundation in Python and advanced tools like H2O.ai and XGBoost, Sijie has successfully developed end-to-end machine learning models that have significantly enhanced operational efficiency. Notably, his innovative approach to fraud detection has resulted in a remarkable 40% reduction in manual review rates, allowing the team to focus on higher-value tasks while maintaining robust security measures.
In addition to fraud detection, Sijie has played a pivotal role in unifying customer onboarding processes across five distinct products. His efforts have led to an impressive 90%+ frictionless auto-approval rate, streamlining the customer experience and accelerating time-to-value for new clients. By pioneering real-time and batched model deployments on various MLOps platforms, including AWS, Datavisor, and Feedzai, he has not only improved the model deployment cycle but also ensured that the solutions are scalable and adaptable to evolving business needs.
Sijie's deep understanding of credit risk management and data-driven decision-making positions him as a key player in the fintech landscape. His commitment to continuous improvement and innovation in machine learning applications not only enhances the security and efficiency of Bill.com’s services but also contributes to the broader goal of fostering trust and reliability in digital financial transactions. As he continues to push the boundaries of what's possible in data science, Sijie remains dedicated to driving impactful results that benefit both the company and its customers.
