About AIReady

Lynn Shaw is a director at Meta, where she leads AI, machine learning, and data science teams. Before that, she held leadership roles in product analytics, ML platforms, and business strategy across multiple major tech companies.

She has built and led teams that ship data-driven products at scale, working across engineering, product, marketing, and business. She knows what it takes to get AI projects from idea to production inside large organizations.

Dr. Su Huang has extensive experience applying analytics, data science, economics, and AI-driven thinking to real-world business and organizational challenges across technology, consulting, education, and product strategy. He is currently working with an AI startup to help clients identify, structure, and solve practical business problems using AI and analytical platforms.

Previously, he worked as an Economist Manager at Amazon, where his work focused on decision-making, forecasting, experimentation, pricing strategy, supply chain optimization, marketing analytics, and people analytics. As the first economist/data scientist supporting Amazon Fresh, he helped design and scale analytical science models and pipelines that contributed to more than $10M in business value across pricing, location strategy, and operational decision-making.

Before joining Amazon, he also gained experience in marketing analytics and consulting-related work, helping organizations better connect data-driven insights with business strategy and decision-making. His broader background across analytics, business communication, and stakeholder management provides a practical perspective on how technical work creates real organizational impact.

In addition to technical and business leadership responsibilities, he also managed the Amazon Economist Mentorship Program, helping junior economists transition from academic research environments into fast-paced industry settings. Throughout his career, he has mentored and managed many semi-technical professionals (such as Business Intelligence Engineers) and helped them successfully transition into more technical and analytical roles such as Data Scientist and Applied Scientist positions. Furthermore, he has successfully referred more than 10 professionals to roles within his own organization and has also helped more than 100 individuals explore and secure career opportunities through his broader professional network and mentorship.

Beyond industry experience, Su also teaches business analytics and quantitative problem solving at the university business school level. He also teaches elementary and middle school students through after-school and summer camp programs focused on real-world problem solving, analytical thinking, and practical AI awareness for the next generation.

Denny has spent years building large-scale distributed systems at top tech companies — backend infrastructure, APIs, cloud-native platforms. He cares about clean architecture, solid code, and shipping things that work reliably at scale.

He has designed systems handling millions of requests, mentored engineers through hard technical problems, and helped teams adopt better practices around CI/CD, microservices, and AI-augmented workflows.

He has guided engineers from junior to senior and staff-level roles, and understands how technical skill, communication, and system thinking come together to drive real career growth.