Kirk McKeown spent 20 years in investment management data and research. He has worked as an analyst for investment firms Hunter Global, Tudor, and Point72. In 2021, he co-founded Carbon Arc, which is building proprietary tech that unlocks insights from petabytes of existing data on a pay-as-you-go basis.

In this episode, Kirk discusses the existing gaps in data markets, how the Carbon Arc model is reshaping that landscape, how the company's insights can be applied to sports teams, and the nature of competitive advantage in the business of information.

Ajay Krishna spent his early career working on systematic trading and big data equities research at Citadel, then served as head of data science and engineering at analytics firm M Science. In 2022, he founded streamOS, where he is building an operating system that ties together data across the entire financial ecosystem.

In this episode, Jake and Ajay talk about the core ideas and incredible potential of streamOS, how he sells the service to buyers who already have data management, and the importance of speed when delivering data insights.

Erkut Sogut holds a doctorate in sports law, and has more than 20 years experience in the football (soccer) agency business. Erkut is the founder of GROW, a player representation agency, and the creator of five important industry newsletters - one released on each day of the working week. His book "How to Become a Football Agent" is now in its third edition.

In this episode, Jake and Erkut discuss the shift of power from clubs to players, the globalization of sports, why recruitment can be totally arbitrary, and the (sometimes unfortunate) increase in multi-club ownership.

Julie Souza is the global head of sports at Amazon Web Services where she drives strategic innovations in data and analytics, generative AI, and next-generation fan experience. She has previously served as vice president of business development and strategy for ESPN and Second Spectrum.

In this episode, Jake and Julie discuss the power of working backwards, specific ways data is making sports safer and more exciting, building vs. buying analytic tools, how hockey is making the most of modern tech, and the coming productization of generative AI.

Michael Parekh is a former partner and managing director at Goldman Sachs. Today, he serves those same roles at MKP Capital Management, focusing on AI and the 4th Tech wave. Michael was using the internet in the 1980s, and has closely watched the evolution of all things digital. He regularly shares his insights with the world on his personal Substack.

In this episode, Jake and Michael discuss Michael's theory of the "AI value stack", why we are at "the beginning of the beginning", what's next after the chat bot, and the ongoing race to build the first AI market moat.

Tim Chen is a managing partner at Essence Venture Capital and part-time advisor to Bessemer Venture Partners. He was a principal engineer at Grid.ai, which created a high-level interface for the Pytorch deep learning network. Cloudera acquired Tim's machine-learning-based startup, Hyperpilot, in 2018.

In this conversation, Tim and Jake drill down on what A.I. businesses and products venture capital is really looking to fund, how to tell the hype from real value, and how to think about a product's long vs. short term disruption of a market.

Ben Rosencranz spent several years as a strategy and analytics manager with E15 before signing on with the Chicago Blackhawks. He is currently using advanced analytics and technology to drive decision making for the team, on and off the ice.

In this conversation, Jake and Ben discuss how he chooses which data problems to tackle, the exciting new changes data is bringing to fan experience and engagement, and how to deal with unrealistic expectations for AI.

Ken Jee is the head of data science for Scouts Consulting Group. In addition to advising senior sports executives, Ken also hosts his own podcast, He also hosts Ken’s Nearest Neighbors podcast, which he describes as "a quest to compile the most complete study on sports performance ever created."

In this episode, Ken discusses what successful data-driven organizations are doing right, starting with a problem vs. starting with a data set, and the tricky question of who gets access to data.