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Intro to the Business of AI: Framing a Business Problem as a Machine Learning Problem
27 February 2022
10:00-11:30 AM EST (UTC -5:00)
Chief Product Officer at Vista Global
Vinay Roy is the Chief Product Officer at Vista Global, a global leader in private jet aviation offering asset-light services to cover all key aspects of private aviation: Guaranteed and On-Demand global flight coverage; aircraft leasing and finance; and advanced aviation technology. He leads a global organization of Product, Analytics, and Data Science. He is responsible for the product roadmap, Product Pricing, and Data science Model to grow demand and Flight operations for the two-sided marketplace of private jets. He is leading the digital transformation of private jet aviation space using various machine learning models for dynamic pricing engines, recommendation engines, and time series forecasting to enable business decisions. Prior to XO Global, he worked at Zeus Living, Apple, Qualcomm, and Nvidia. He has two patents in the field of Autonomous vehicle and P2P communication. He is also a lead instructor at UC Berkeley, ExecEd Program, where he teaches Machine learning, Business of Artificial Intelligence, Product Pricing, International Marketing, and Digital Transformation to global cohorts of business and technical executives.
In his spare time, he enjoys reading, teaching, and playing soccer. He is an MBA from Haas School of Business, UC Berkeley, and has a Masters in Computers & Mathematics from the Indian Institute of Technology, India.
The commoditization of machine learning has happened at an unprecedented rate so much so that it is difficult to find a company — big or small, David or Goliath, that is not exploring Machine learning as a means to stay relevant in this rapidly changing business environment. This has led to the rise of data science arms in most companies driving product ideas and improvement. As a result, data science teams are becoming a strategic arm of the company and most companies claim themselves to be data-driven. However, many organizations struggle to traverse the path from wanting to use AI to unlock hidden business values to becoming ML leaders in their space. We will look at what are some tech and cultural blockers that limit the success of AI/ML models across the organization. We will discuss a framework to think about the AI Maturity curve in your organization and steps to frame a business problem into a machine learning problem to enable growth. This is handy for business, tech, and data science leaders to collaborate with each other and build a data fluent organization. This webinar will also cover growth hacking tips for a career in Data Science and Product Management.