AI is transforming data careers. Roles once centered on modeling and feature engineering are evolving into positions that involve building AI products, crafting prompts, and managing workflows shaped by automation and augmentation. In this panel discussion, ambassadors from Women in Data Science (WiDS) share how they have adapted through this shift—turning personal experiments into company practices, navigating uncertainty, and redefining their professional identities. They’ll also discuss how to future-proof your career by integrating AI into your daily work and career growth strategy. Attendees will leave with a clearer view of how AI is reshaping data careers and practical ideas for how to evolve their own skills, direction, and confidence in an era where AI is not replacing, but redefining, human expertise.

This tutorial tackles a fundamental challenge in modern AI development: creating a standardized, reusable way for AI agents to interact with the outside world. We will explore the Model Context Protocol (MCP) designed to connect AI agents with external systems providing tools, data, and workflows. This session provides a first-principles understanding of the protocol, by building an MCP server from scratch, attendees will learn the core mechanics of the protocol's data layer: lifecycle management, capability negotiation, and the implementation of server-side "primitives." The goal is to empower attendees to build their own MCP-compliant services, enabling their data and tools to be used by a growing ecosystem of AI applications.