A1942
Title: Data science in tech: Driving product impact from telemetry to the AI era
Authors: Meeyoung Park - Google (United States) [presenting]
Abstract: In the modern tech ecosystem, data science is the engine driving strategic differentiation. Data-driven paradigms have fundamentally transformed product development and operations through critical pillars including robust telemetry, rigorous experimentation, continuous product optimization, and deep customer insights. By converting massive datasets into actionable intelligence, data science has evolved from a supportive analytical function into a core driver of business strategy and product innovation. Simultaneously, the rapid ascent of Artificial Intelligence and Large Language Models has triggered a profound shift in the data science landscape, significantly expanding the traditional boundaries of data exploration and predictive modeling. Navigating this transition successfully requires additional skillsets and mindsets. Data scientists are pivoting from builders of isolated models to architects of intelligent systems, cultivating a strong sense of product ownership, adaptability, and the ability to balance the nuances of AI orchestration with an enduring need for statistical rigor. Drawing from hands-on and leadership experiences within Google Cloud, the historical impact of data science in tech, its modern evolution alongside generative AI, and the future-ready capabilities required to lead in this new era are examined.
