Ed Wiley is a high-visibility senior executive with >25 years of building, leading, and advising world-class machine learning, AI, and data science teams & projects at companies at stages from startup to Fortune 50. An active member of the AI & data science communities, Ed regularly presents at national and international conferences and workshops.
Key professional experiences include:
⇒ Built and led the first Data Science practice as Chief Data Scientist at Sears Holdings (NASDAQ: SHLD)
⇒ Built and led the first Big Data practice at Seagate Technology (NASDAQ: STX)
⇒ Created and delivered Udacity’s “Data Science for Business Leaders” executive program
⇒ Author of forthcoming (Q2 2024) book “AI: From Buzzword to Business Function. A Leader’s Playbook for Bringing AI, Machine Learning, and Data Science to your Business”
⇒ McKinsey-trained business strategist and executive consultant
⇒ Stanford-educated Ph.D. Statistician/Data Scientist
⇒ Chair, Research & Evaluation Methodology doctoral program at U. of Colorado
⇒ Advisor to federal governmental agencies/projects in Colombia, Germany, and U.S.
⇒ Track record of successful delivery of production, enterprise-scale data/analytics products
Few careers in AI have been as long and varied as Ed’s. Ed has worked with AI as a doctoral researcher, as a McKinsey consultant, as a Fortune 50 executive, as a professor and doctoral program Chair, as a partner with the DEA and other federal agencies, and as a founder and executive in multiple startups. Ed and his teams have wrestled with the thorny issues of using AI across countless contexts. He knows what’s critical to consider in building an AI practice or executing an AI project, and also helps guard against missteps and pitfalls that doom your AI efforts. After working with AI across such varied contexts, Ed knows what to do – and what NOT to do – when working with AI.
Ed’s “3 P’s” framework for bringing AI to the business specifically focuses on the People, Platform, and Processes necessary for a world-class AI function:
–People (identifying roles for which to hire; recruiting, developing and retaining talent)
–Platform (optimizing data access/storage; machine learning platform; cloud vs. on prem; includes ‘Build vs. Buy’)
–Processes (driving AI initiatives and teams as part of software development; organizing the AI practice w/in the business)
Contact Ed