How EDF Built Data Foundations for AI Success

Abstract

This presentation explores how EDF has established a robust data foundation to enable AI success. It covers the implementation of a Snowflake Data Lake, the adoption of a federated data engineering approach, and the development of the MLOps platform ICE, which leverages Snowpark and SageMaker for machine learning deployment.

The session will highlight real-world use cases, governance strategies, and future plans to enhance AI capabilities. Attendees will gain insights into best practices, challenges overcome, and the business impact of EDF’s data-driven AI strategy.

About the speaker

Rebecca Vickery, Senior Leader of Customer Insight

Rebecca is the Senior Leader of EDF's Customer Insight team, a Data Science and Research team dedicated to driving better customer engagement through data insights. With over 16 years of experience in the field of Data Science Rebecca mentors and leads her team to develop models for segmentation, targeting and personalisation. Passionate about technology and improving customer experiences she is currently leading a project to embed a new Customer Engagement Platform (CEP) that will streamline and improve customer communications across the organisation.

Outside of her day job Rebecca is a strong advocate for improving gender diversity in the data and tech fields. She also regularly publishes articles designed to help people break into the field of Data Science on her blog hosted on Medium.com.