Plaid

Investigate fraud patterns and model errors to identify new signals, improve detection, and expand coverage.Develop training datasets and predictive features while addressing incomplete labels, class imbalance, data leakage, and changing fraud behavior.Design, train, tune, and evaluate models including gradient-boosted trees and neural networks.Design experiments comparing model per

Research and prototype advanced approaches across graph machine learning, sequential modeling, and multimodal learning for fraud detection.Own and execute a research roadmap that turns innovative ideas and prototypes into production solutions with measurable product and customer impact.Design rigorous experiments and evaluation methodologies reflecting real-world fraud dynamics.Part

Build and scale machine learning systems supporting a growing fraud detection product.Develop high-performance feature computation and online inference pipelines for production ML systems.Build observability, monitoring, reliability, and automated debugging capabilities.Develop foundational ML capabilities using Plaid’s financial network data to detect and prevent fraud.Solve techni