Data Science Leaders

How do you enable AI, data science and analytics on petabyte-scale data, with extremely stringent privacy and security requirements? This episode comes to you from the RevX-New York conference where we had a fireside chat with Ivan Black - Director in charge of ML, AI, and analytics platforms at the US financial services regulator FINRA .  Join us as we discuss: The challenges of enabling AI on ma...

How do you craft and implement a strategy to transform an organization with AI? Not just to build a growing portfolio of successful AI projects, but to fundamentally re-engineer the organization’s core processes, to radically increase productivity, to overhaul the company’s tech stack, and to prepare it for a future of AI-driven competition. In this episode, Akshaya Murthy , who leads the AI effor...

AI leaders. Why do we need them? How do you become one? And above all, how do you keep your job as one? In this episode, we are joined by guest speaker Mike Gualtieri , VP and Principal Analyst at Forrester, and we unpack the opportunities, pitfalls, and best practices of the AI leader role. He shares the pivotal role of AI leaders in catalyzing organizational transformation, their unique skill se...

GenAI is evolving at a breakneck pace, matched only by the startups that are looking to commercialize it. So what better way to understand the latest GenAI trends than to ask a venture capitalist specializing in AI?  In this episode, we speak with James Cham , partner at Bloomberg Beta , about the state of GenAI – where it is delivering value today – and the challenges preventing firms from moving...

A human being consists of billions of cells, each with the same genetic code but interacting in a myriad ways that can eventually translate into disease. Understanding and treating that disease is, in essence, a data problem. But how do you unlock that data and how do you change an organization to systematically use that data to improve decision-making and accelerate drug discovery?  In this episo...

Trip planning may well be the perfect AI use case. Too much information, too many combinations, and too little time —for humans, but not for Tripadvisor’s AI Trips. In this episode Rahul Todkar , VP Head of Data and AI, shares the secrets to building a trusted GenAI solution at internet scale and discusses the similarities and differences between data leadership roles at digitally native companies...

Wouldn’t it be great if there was a commonly agreed-upon framework for executing all AI projects successfully? Well, there isn’t one. However, there is CRISP-DM, the antediluvian “Cross-Industry Standard Process for Data Mining”, but you need to expand, modernize and adapt this framework for success at your organization. In this episode from the archive, Dave Cole interviews David Von Dollen , for...

What’s just as important as the government keeping us safe from AI? Government leveraging AI to keep us safe! In this episode, we interview Joel Meyer – former head of strategy at the Department of Homeland Security (DHS) and the person who drove the creation of the DHS AI Task Force. Joel shares how they identified key areas where they could apply AI to improve national safety and security, such...

There is no such thing as an AI drug, but AI and ML-models are driving the next wave of new treatments. In this episode, Brandon Allgood , Chief Data Officer at FogPharma and serial entrepreneur at the intersection of ML and Biopharma, shares his insights on how AI is disrupting the traditional process of drug discovery and development. Join us as we discuss: Why AI is so powerful for drug discove...

What’s the biggest problem in AI today? It’s that far too few projects make it to deployment. In this episode, Eric Siegel , founder of the long-running Machine Learning Week conference and creator of the first (and perhaps only) ML music video , tells us about his new book, The AI Playbook and the bizML framework for aligning stakeholders and maximizing the chance for deployment and impact. Join...

The biggest challenges to driving impact with AI have little to do with AI and everything to do with humans. Nowhere is this greater than with GenAI where myths and misconceptions abound as to how organizations should be designing, developing and operationalizing GenAI-based applications. In this episode with Rowan Curran , industry analyst at Forrester Research , we debunk the most harmful myths...

Imagine Generative AI handling tens of thousands of conversations with your customers daily. Science fiction? Not at Bolt where this has been in production since the summer of 2023. In this episode, Mikhail Korolev – head of the data science team at Bolt’s food delivery service – shares the challenges and hard earned best practices for operationalizing a GenAI application that dramatically lowers...

2023 has been an exciting year for AI, but it’s nothing in comparison to what we will see in 2024! Expect to see sensational successes amid the debris of projects that were set up for failure, a flowering of predictive AI, and the emergence of the scariest thing in AI to date (EU regulation). Tune in to this episode where Dr. Kjell Carlsson shares his top predictions for AI in 2024 and get ready f...

ChatGPT wasn’t the beginning of generative AI, but it did spark the GenAI revolution. Now, one year since it was launched, how much progress have we made, what impact is GenAI delivering, what are the real risks, and what developments are just around the corner? Join this session with the titan of the data science community, Anaconda CEO Peter Wang , and Dr. Kjell Carlsson, Head of AI Strategy at...

How do you achieve success as a Chief Data Officer? It is a role that is more important, yet more challenging, than it has ever been, with a rapidly expanding set of expectations from stakeholders in every part of the business. Here to help us understand the CDO role, its evolution, and the keys to success is Gary Barr , Global Chief Data Officer at Legal & General Investment Management (LGIM)...

Most experts agree that AI isn’t about replacing human intelligence, but about improving it. When it comes to education, we should take this literally . In this episode we discuss how to use AI to transform how we learn with Stephen Kosslyn , President of Active Learning Sciences and Founder and Chief Academic Officer of Foundry College . Stephen brings unparalleled expertise when it comes to usin...

How do you implement an enterprise-grade GenAI application that serves millions of users a day? By focusing your application and building the capabilities for operationalizing it at scale. Join our upcoming fireside chat with Domino's SVP of Product, Chris Lauren , who will share lessons learned while operationalizing the world’s first enterprise-grade GenAI application to be used on a global scal...

Every organization has an abundance of outlier detection use cases, but how do you turn them into repeatable, scalable AI products that drive a virtuous cycle of adoption and impact? To answer this question, Jan Zirnstein , Senior Data Science Director at Honeywell ,. shares their best practices for successfully driving value using anomaly detection, how to build trust with stakeholders, and the i...

AI has enormous potential for good, not least in helping us make more ethical, sustainable decisions as investors and consumers. In this week’s episode Ron Potok , Head of Data Science at Clarity AI , explains how AI helps us overcome the challenges of collecting, normalizing and assessing Environmental, Social and Governance (ESG) data and making that data useful and convenient to humans when mak...

How do you trust black-box AI models with decisions that will make-or-break your business? This week we speak with Gregory Zuckerman -- special writer at the Wall Street Journal and author of The New York Times bestseller of The Man Who Solved the Market -- to find out how the pioneers in algorithmic trading learned to stop worrying and trust their AI systems. Join us as we discuss: How trust in A...

Who doesn’t have a data science talent gap? Anyone? Most organizations struggle to realize their AI ambitions because of a lack of data science skills, a disconnect between the technology and the business domain, and a lack of leadership experience with AI. Halliburton has been solving all three of these challenges with one of the earliest and largest corporate data science programs in the energy...

It’s been said: “When everything is important, nothing is important.” So how do you succeed with AI-driven transformation where everything – across people, process, and technology – is important? It requires leadership, a deliberate strategy, and ongoing organizational change. Here to share insight on these transformational challenges and best-practices are Jen Stave and Catherine Feldman from the...

Generative AI is here and, unless you’ve been cloistered in a cave, you already know it’s making waves in nearly every industry. But when it comes to this shiny new technology, separating fact from fiction can become quite a challenge. Luckily, in this episode, Rowan Curran , Analyst at Forrester , joins the show to demystify the latest leaps in AI tech, help you apply it to your business today, a...

“It is on the shoulders of leaders that they build and maintain an ethical AI risk program.” That’s the message Reid Blackman – author of “Ethical Machines” and founder CEO at Virtue Consultants – shares in this episode. He discusses the real ethical AI concerns — blackbox models, bias, hallucinations, privacy violations and more — and explains the crucial need for leadership accountability, buy-i...

When it comes to driving business impact with AI, there are no silver bullets, but data science product management comes pretty close. It could well be the key to bridging the gap between business and technical teams, designing solutions to meet the business need, spurring ideas from experimentation to implementation, and driving continuous improvement. But how do you build a product management ca...