Data Engineering for Streamlining the Data Science Developer Experience - DE4AI

Explore the challenges and solutions in data engineering for optimizing the data science developer experience in this 12-minute talk by Aishwarya Joshi from Chime. Discover how to enable efficient feature engineering and deployment for low-latency inference serving in fraud detection models. Learn about the infrastructure and frameworks supporting feature storage, ingestion, and streamlined development workflows. Gain insights into overcoming scaling and data quality challenges while maintaining feature parity between training and real-time inference. Understand the critical role of data engineering in enhancing the efficiency and effectiveness of data science teams working on time-sensitive applications like financial fraud detection.