Data Science Leaders
Data Science Leaders is a podcast for executives who are using machine learning and artificial intelligence to tackle major challenges. Host Thomas Been interviews pioneering data science leaders and industry watchers, sharing real stories, breakthrough strategies, and insights to help listeners build their own model for enterprise data science success.
Episodes
The Cave: Pharma's Data Problem
Dave Johnson’s first pharma job wasn't in a lab. It was in a room, dark and cramped, stacked floor to ceiling with 30 years of decaying discovery chemistry data on every storage medium imaginable.They called it “the cave.”A physicist turned data leader, Dave has spent two decades solving the same problem: scientific data is generated for one purpose, poorly captured, and left abandoned.Now co-foun
Turning Governance Into the “Yes” Guys
When Cindy Tu first stepped onto a conference stage, it wasn’t part of a long-term plan. It was a turning point. A single speaking invitation shifted her role from quietly reviewing AI systems to actively shaping how governance is practiced across financial services. With a background spanning IT, data, and audit, Cindy brought a rare systems-level view to the table.Now a rising voice in enterpris
Building Trust for Transformation in Enterprise AI
When Shub Agarwal joined an early conversational AI startup, he was building products in uncharted territory with emerging technology few had heard of. By late 2019, Google and Meta were aggressively recruiting him. But a sudden personal loss made him rethink his priorities, leadership, and the impact he wanted to create.From fast-growth startups to a financial regulator, he's codified a nine-step
Engineering the Future of Health with AI and Data
Daniel Kraft, physician-scientist and founder of NextMed Health, joins Domino’s Chris McSpiritt to discuss how AI, data convergence, and systems thinking are accelerating healthcare’s shift from reactive treatment to proactive, personalized care. With a background spanning regenerative therapies, digital health, and aerospace medicine, Daniel offers a wide-lens view of the challenges and opportuni
The Rise of the Self-Driving Organization
As organizations race to become AI-driven, data has emerged not just as a resource, but as a strategic advantage. In this episode, Kjell Carlsson sits down with Doug Laney, author of Infonomics and Data Juice, to explore how generative AI is accelerating the journey toward data monetization and organizational autonomy. Doug shares why traditional approaches to data management no longer suffice, ho
The Cultural Shifts That Power AI Adoption
AI strategy isn't just about technology. It's about transformation.In this episode, CDAO expert, Dr. Shahram Ebadollahi, joins to discuss what it takes to lead AI in an enterprise and why that leadership must go far beyond just selecting the right tools or models. Drawing on his experience building AI teams, Shahram explains why the Chief AI Officer role is one of the most complex, and most critic
The AI Race: Predictions for AI in National Security & the Public Sector
What does the global race for AI look like? How has the US Department of Defense been adopting AI by engaging the private sector? And how should we expect AI policy to shift under the new administration? In this episode – the last in our series on the future of AI – guest host Joel Meyer, President of Public Sector at Domino, sits down with General Jack Shanahan (Ret.) former Director o
The Future of Enterprise AI? AI in Production!
What does the near term future of Enterprise AI look like? A scramble to get valuable, cost-effective, enterprise-grade AI solutions into production, with rigorous governance at scale. If that sounds like a tall order - that’s because it is! However, large advanced organizations (yes, even outside of the tech sector) are already seeing success deploying AI solutions and we can expect the pace to a
The Silent Future of AI in Financial Services
AI is transforming financial services and insurance, but rarely in the headline-grabbing ways you might expect. From intelligent process automation to fraud detection and risk management, AI is being embedded across operations, but as AI adoption grows, so do the challenges—cybercrime, rapid technological changes, and ever-evolving regulatory frameworks.In this episode we sit down with Adam Gale,
Pharma Is the New Tech: The Future of AI in Life Sciences
AI is transforming drug discovery and clinical trials, making what was once cutting-edge the new standard. Pharma companies are evolving into tech companies, leveraging AI to revolutionize every phase of drug development.In this episode, Chris McSpiritt, VP of Life Sciences Strategy at Domino, discusses how AI is no longer a niche capability for select firms but an essential capability for all bio
AI Predictions for 2025: The Boogeyman, Agentic AI & Governance
What’s next for artificial intelligence in 2025? In this episode, Dr. Kjell Carlsson delivers his annual predictions about the immediate future of AI. From AI becoming the universal corporate scapegoat to the rebranding of generative AI as "agentic AI.” Discover why commercial AI solutions remain scarce, the pivotal role of workforce upskilling in achieving transformative AI outcomes, and how gove
Realizing AI Value Through Governance in Insurance
Innovation and AI governance aren’t at odds. Done properly, governance practices can be the key to accelerating implementation of even the latest GenAI use cases. In this interview from RevX London with Raj Mukherjee, Head of Data Science and AI at Direct Line Group, we find out how they embraced the principles of a lean startup, adopted a product mindset and became the first major insurance compa
Mastering AI Governance with Forrester & the Federal Reserve
How can organizations drive transformative AI innovation while effectively managing its inherent risks? Is governance a bottleneck or can it become a catalyst for AI success?In this webinar, we explore the critical role of AI governance with Brandon Purcell, VP Principal Analyst at Forrester Research, and Theo Linnemann, Data Scientist at the Federal Reserve Bank of New York. Together, they share
Crossover: Ethical Machines and AI Governance
This episode is a collaboration with the Ethical Machines podcast featuring Reid Blackman — CEO of the AI ethical risk consultancy Virtue — and Nick Elprin, cofounder and CEO of Domino Data Lab. Join us as they discuss:The differences between AI ethics and AI governanceHow the AI governance challenges have changed (and where they haven’t)The people, process and technology solutions for genAI gover
AI Transformation in Government: Lessons from Unit X
Think you have a hard time driving AI adoption in your organization? Try driving AI transformation in the largest, most regulated organization on the planet – the Pentagon. In this episode, we sit down with Dr. Chris Kirchhoff – co-author of Unit X: How the Pentagon and Silicon Valley are Transforming the Future of War and former Director of Strategic Planning for the National Security Council – t
The EU AI Act: Key Strategies for Regulatory Compliance
The EU AI Act, is it the first step towards comprehensive AI regulation that will make us all safer, or is it the scariest thing in AI today, or both?In this episode we speak with Adam Gale, Field CTO for AI and Regulatory Compliance at NetApp, to demystify the EU AI act and discuss future-proof strategies to ensure compliance.Join us as we discuss:The core requirements of the act and how they imp
AI Governance in Action: Lessons from the Trenches
AI governance is no longer a hypothetical consideration—it's critical not only to meet regulatory requirements but also to build trust, drive adoption, and deliver tangible impact with AI. In this episode, we bring together experts Jared Vaudrey and Dr. Dylan Bobby Storey, who have spent years developing AI solutions in heavily regulated industries. They share their hard-won insights on the realit
Demystifying the Top 5 Questions of AI Governance
AI governance is more important than ever, but confusion reigns about basic questions such as: what it is, why it is important and what we should do about it. As an AI, data science, or business leader, you need to dispel these governance misconceptions in order to manage AI risk and ensure the safety and reliability necessary to drive adoption and impact. The ability of your organization to drive
Operationalizing privacy in the age of AI
Data privacy - why is it so important in the age of AI, why is it so difficult, and what should we be doing to improve it in our organizations?In this episode we speak with Dr. Rebecca Balebako, privacy engineer and Chief Privacy Officer at Lotic.ai, about why AI makes privacy more important than ever, the common misconceptions around data protection, who should own privacy, and the benefits and l
Optimizing Your Architecture for AI Innovation: BARC Survey Results
What capabilities do you need to take advantage of AI and what changes will you need to make to your IT architecture? Well, let’s look at the data.In this episode, Shawn Rogers, CEO and Fellow at BARC US, shares the results of their survey on how enterprises are optimizing their architecture for AI innovation. Shawn unpacks data on everything from the biggest obstacles to delivering AI impact to h
Driving Digital Strategy with AI at OneAmerica
How do you drive digital strategy and transformation with AI? Do you need an AI strategy or a business strategy that intelligently leverages AI?In this episode, we delve into the challenge of driving transformation with AI in insurance with Fu'ad Butt, VP Head of Digital Strategy and Automation at OneAmerica. Fu’ad shares his best practices for identifying and executing AI projects. These range fr
AI-driven Marketing, Optimization, Consciousness and CAIOs
AI is disrupting marketing, but the biggest threat isn’t AI systems misbehaving, it is the unintended consequences of AI systems performing exactly what they were intended to do.In this interview with Dr. Daniel Hulme, Chief AI Officer at WPP and CEO of Satalia, we discuss the ways that AI is transforming marketing – from accelerating content creation and maximizing activation to exploring the cre
Trust and faster AI time to value in manufacturing at IFF
How do you deliver impact with AI and ML and cut development time by weeks and even months? By understanding your customer, building trust, and managing risk. Done well, effective and responsible AI practices can be the secret to faster implementation, adoption, and performance at lower cost and risk.In this episode with Dr. Alex Manasson, Data Science Leader for the Americas at International Flav
How to Make Responsible AI Happen: A Historical View
How do you deliver value with responsible AI, who is responsible for it, how do you put it into practice, and could we use AI to make our organizations more ethical? This episode comes to you from the RevX conference in London, where we asked these questions of Chris Wiggins, Chief Data Scientist at the New York Times. He is also Professor of Applied Mathematics at Columbia University and author
Efficient Data Pipelines for AI and a Healthier World
AI is not all about the data, however, your ability to develop and deploy efficient data pipelines is absolutely critical for unlocking the power of AI at scale. But how do you manage modern data pipelines for AI and how do you deal with fragmented ecosystems and spiraling costs? In this episode, brought to you from the RevX Philadelphia conference, Richard Swakla, AI/ML Specialist at NetApp, joi
Enabling AI on Enormous Financial Datasets at FINRA
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 massiv
Developing a Strategy for AI Transformation at Zendesk
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 efforts
Surviving and Thriving as an AI Leader in a GenAI World
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 set
Unlocking the Disruptive Potential of Generative AI: A VC Perspective
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 fr
Overcoming the Data Challenges of AI-driven Drug Discovery
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 episod
AI Will Plan Your Next Vacation: GenAI at Tripadvisor
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
From the Archive: A Hybrid Approach to Accelerating the Model Lifecycle
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, forme
Unlocking AI in the Public Sector
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 a
Disrupting Drug Discovery and Development With AI
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 discovery
Mastering the Rare Art of ML Deployment
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 us
Shattering the Myths of GenAI: Interview with Forrester Analyst Rowan Curran
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 an
More Human Than Human? GenAI Customer Service at Bolt
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
AI in 2024: Predictions on the Future of the AI Revolution
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
The State and Future of Generative AI: Reflections on the Anniversary of ChatGPT with Anaconda CEO Peter Wang
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 D
CDOs: Changing the Operating Model for Data & AI Transformation
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).
Transforming Education with Generative AI and Active Learning
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 using A
“Lessons from the First GenAI Killer App"
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 scale,
Honeywell: Delivering on the Power of Outlier Detection
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 impo
Making Better Sustainability Decisions with AI
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 makin
Celebrity Guest Gregory Zuckerman: Trusting AI to Make the Decisions
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 AI
Solving the AI Talent Gap: Upskilling at Scale at Halliburton
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 s
The AI Innovator’s Dilemma: Insights from Harvard’s D^3 Institute
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 th
Get the Most Out of Generative AI
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, and
Celebrity Guest Reid Blackman: Who’s Responsible for Responsible AI?
“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
Output to Outcomes: AI Product Management at Verizon
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
Celebrity Guest Steven Levy: AI, a mirror to human intelligence
What’s different about the AI wave today versus the 1980s and what do the latest advances reveal about our human intelligence? We’re behind the scenes at Rev4 with Steven Levy, best selling author and Editor at Large at WIRED. Steven shares insights he’s built over the past four decades writing about AI and the people (like Marvin Minskey) and companies (like Google and Facebook) that have brought
Season 2: Host to Host
Who’s the best person to share the secrets of Data Science leaders? Try someone who has spent the last year interviewing them! Former industry analyst and new host of the podcast, Dr. Kjell Carlsson, interviews Dave Cole on all surprising things he’s learned in hosting the nearly 50 episodes of season 1. The two delve into various topics, such as how you may unexpectedly become a data science lead
What It Takes to Productize Next-Gen AI on a Global Scale (Srujana Kaddevarmuth, Senior Director of Data & Machine Learning Programs, Walmar
What does it take to turn the latest advances in AI into products that deliver business impact at Walmart levels of global scale?Srujana Kaddevarmuth is the Senior Director of Data & Machine Learning Programs at Walmart Global Tech. Her team drives data strategy and grapples with data science productization every day. With millions of employees, hundreds of millions of customers, and petabytes of
Help Me Help You: Forging Productive Partnerships with Business Stakeholders (Sunil Kumar Vuppala, Director of Global Artificial Intelligenc
There’s tremendous value in pure data science research. In an enterprise context, however, it all comes down to how learnings and insights from that research can help advance business growth, customer experience, and product innovation.Sunil Kumar Vuppala is the Director of the Global Artificial Intelligence Accelerator at Ericsson. His career journey from a researcher role to data science leaders
Change Management Strategies for Data & Analytics Transformations (Michal Levitzky Head of Data & Analytics - CDO, Migdal Group)
Large enterprises will always have some internal groups that are more change-averse than others. But progress often necessitates change, and how well you navigate the change management process can make or break your success as a leader.Michal Levitzky is the Head of Data & Analytics (CDO) at Migdal Group, a leading insurance and finance company in Israel. Michal has spearheaded the introduction of
A Hybrid Approach to Accelerating the Model Lifecycle (David Von Dollen, Head of AI, Volkswagen of America)
Without a clearly defined methodology, complex projects with multiple technical and business stakeholders often fall apart. The risk is especially high when trying to scale data science work in an enterprise organization. That’s why David Von Dollen, Head of AI at Volkswagen of America, integrated agile methodology with CRISP-DM to help his team navigate roadblocks and accelerate progress on the p
Giving Back and Building Your Brand as a Data Science Leader (Sidney Madison Prescott, Global Head of Intelligent Automation - RPA, AI, ML,
Even with the recent rise of specialized data science degree programs, top-notch data science talent can come from anywhere. Those in leadership positions have a duty to share their knowledge and support aspiring data scientists, regardless of the unique path that brought them to the field. Sidney Madison Prescott, Global Head of Intelligent Automation (RPA, AI, ML) at Spotify, has made a habit of
Governing Models and Structuring Teams in Highly Regulated Industries (Anju Gupta, VP Data Science & Analytics, Northwestern Mutual)
Model governance is vital, especially in heavily regulated industries like insurance.Strong governance can help ensure that key models are reproducible, explainable, and auditable—all important factors for both internal model development workflows and for external regulatory compliance. But the best governance strategy isn’t always obvious.Anju Gupta, VP Data Science & Analytics at Northwestern Mu
How to Operationalize, Scale, and Measure AI in Life Sciences (Sidd Bhattacharya, Director of Healthcare Analytics & AI, PwC)
In every industry, people consume data. They work to understand what it can tell them in order to make smarter decisions.But the nature of data in the world of life sciences presents some unique challenges—and opportunities—for data science.In this episode, Sidd Bhattacharya, Director of Healthcare Analytics & AI at PwC, dives deep into these dynamics and shares his perspective on how leaders can
Getting to Ground Truth with Strategies from ML in Electronics Manufacturing (Alon Malki, Senior Director of Data Science, NI)
Many people assume that once you establish a manufacturing line, the hard work is done and things remain relatively static. The reality, especially in electronics manufacturing, is entirely different.Constantly changing data streams and endlessly dynamic variables present some unique challenges for data scientists in the field. But there are lessons on data sharing, model adoption, and real-time i
Elevating Your Team as Strategic Business Partners (Indy Mondal, Senior Director of Data Science, AI & Product Insights, DocuSign)
When your data science team is consistently more reactive than proactive in addressing business challenges, it can be difficult to be seen as strategic partners.But by prioritizing building business domain expertise and always asking about the “why” behind any request, you’ll start to build a rapport and change the nature of the relationship.In this episode, Indy Mondal, Senior Director of Data Sc
A Journey Through the Data Science & Analytics Value Chain (Nancy Hersh, Chief Data Officer, Arcadia)
To create sustainable business value, data scientists need to navigate all the elements of what this episode’s guest has dubbed “the data science and analytics value chain.”So what are those elements? And how can you ensure you hire and develop the team that delivers on each one with every single data science project?Nancy Hersh, Chief Data Officer at Arcadia, joins the show to break it all down.W
Decoding Human Behavior and Well-Being through Data Science (Takuya Kitagawa, Chief Data Officer & Managing Executive Officer, Rakuten Group
The coding, models, and experiments inherent in data science work may have more to do with understanding human well-being than you think.Machine learning and AI can be applied in ways big and small to further our understanding of human behavior—and influence our well-being.Takuya Kitagawa, Chief Data Officer & Managing Executive Officer at Rakuten Group, believes there must be a shift toward focus
Motivating Teams and Combating Bias in Healthcare Data Science (Vikram Bandugula, Senior Director of Data Science, Anthem)
Bias is an ever-present enemy of sound data science in healthcare.Without proactive measures to mitigate bias in the data used to build and train models, real people can bear the brunt of potentially life-altering negative consequences.Vikram Bandugula, Senior Director of Data Science at Anthem, knows this issue intimately from his extensive experience in healthcare. He joins the show to share his
Data in the DNA: Breaking Down the Autonomous Enterprise (Janet George, Enterprise AI Leader & Author)
Is your team mining all available data to inform your business strategy and grow revenue? Is your company prepared to compete against others who are?If you’re like most, the answer is probably no.How can you future-proof your organization and take steps toward an autonomous enterprise?Janet George is an enterprise AI leader and author with experience across companies including Oracle, Apple, Accen
Embedding Responsible AI in Your Models and Your Team (Anand Rao, Global Artificial Intelligence Lead, PwC)
Who uses the models that we create and how do they use them? Those key questions underpin the notion of responsible AI. Since algorithms can have a significant societal impact, it’s vital that data scientists are aware of the broader context in which they may be applied. In this episode, Anand Rao, Global Artificial Intelligence Lead at PwC, breaks down why responsible AI should be an important co
Supply Chain Solutions & the Role of the ML Engineer (Karin Chu, VP Data Science & Digital Analytics, Peapod Digital Labs)
When highly disruptive events like the COVID-19 pandemic occur, data science teams may have to throw historical data out the window. Models trained on what happened in the past simply don’t work in a radically different present.In this episode, Karin Chu, VP Data Science and Digital Analytics at Peapod Digital Labs, discusses how her team is tackling that challenge head on, particularly as the glo
Legal Analytics: Winning Business, Winning Cases, and Winning Over Your General Counsel (Peter Geovanes, Head of Data Strategy, AI & Analyti
Legal work may not be an obvious application of data science to many advanced analytics leaders. But that should change.In this episode, Peter Geovanes, Head of Data Strategy, AI & Analytics at Winston & Strawn, breaks down the nuts and bolts of legal analytics and how it’s revolutionizing the way law firms win new business—and cases. Plus, he shares insight on the types of legal challenges data s
Empowering Big Teams to Take on Even Bigger ML Challenges (Jan Neumann, Executive Director, Machine Learning, Comcast)
Managing a large enterprise team of data scientists can be a complicated undertaking. There are so many opportunities, big and small, to serve the business with AI and machine learning. How do you ensure your teams are focused on the big picture without getting bogged down in the minutiae of the day to day?Jan Neumann, Executive Director, Machine Learning at Comcast, leads a team of about 300 data
Change Management: Winning Over AI Skeptics in Banking & Beyond (Chun Schiros, SVP, Head of Enterprise Data Science Group, Regions Bank)
As compute capability continues to expand, the banking industry is turning more and more to data science to enable better customer experiences.Use cases have proliferated, from product recommendation engines to predictive customer retention alerts. These innovations can drive real business value, but managing the rollout of process and technology changes always presents interesting challenges.In t
To Patent or Not to Patent? How to Weigh the Options for Your Team (Kli Pappas, Associate Director of Global Analytics, Colgate-Palmolive)
Should your team patent its data science work? With open source such an important part of the data science community, patents almost seem antithetical to the ethos of the field itself.But it turns out, there are some very good reasons to pursue data science patents in business.In this episode, Kli Pappas, Associate Director of Global Analytics at Colgate-Palmolive, shares his team's process for de
How a Centralized Data Science “Nerve Center” Can Power Global Impact (Tim Suhling, VP Global Business Intelligence, Ingram Micro)
There are many ways to structure a data science function in a global enterprise. But what’s been the winning strategy for global technology distributor Ingram Micro? Creating a data science “nerve center.”Centralizing data science talent has helped elevate analytics at Ingram Micro to better solve complex business problems using machine learning and AI.In this episode, Tim Suhling, VP Global Busin
Scaling Data Science Value with Cross-Functional Teams (Jayesh Govindarajan, SVP Data Science & Engineering, Salesforce)
To embed models into SaaS platforms at scale, it pays to have a cross-functional team—software engineers, UX designers, data scientists, machine learning engineers—all working together.That collaboration allows you to tackle hard challenges around scaling models to work across hundreds of thousands of customers. And it enables you to build something that offers tremendous value across many differe
Modernizing Healthcare Through Data Science and Digital Transformation (Kaushik Raha, VP Data Science & Health Content Operations, Elsevier)
In healthcare, only 14% of scientific discoveries actually make it into clinical practice. But data science, in lockstep with the digital transformation, is helping to change that.As healthcare data and clinical studies transition to digital form, the opportunity to use data science and AI to generate insights and recommend treatment pathways is greater than ever. And the ability to make healthcar
How Data Science Teams Are Going Deeper with Proof of Value (Nimit Jain, Head of Data Science, Novartis)
As business leaders become more educated on the value that machine learning can deliver, the demands on data science teams only become greater. Business stakeholders are now interested in much more than the accuracy of predictive models. They’re asking questions about productionization, scalability, and bottom line ROI.In this episode, Nimit Jain, Head of Data Science at Novartis, joins the show t
Why It Pays to Stand Out From the Crowd in Data Science (Bob Bress, Head of Data Science, FreeWheel)
Talent is pouring into data science, even though it always seems like there’s not enough to meet demand. Learning opportunities for people getting into the field have exploded in just the past decade. That means standing out from the crowd—both as a leader and as a practitioner—has become more important than ever before.In this episode, Bob Bress, Head of Data Science at FreeWheel, explains how pr
Tracking Business Value with Data Science Portfolio Management (Katya Hall, Director of Enterprise Analytics, McKesson)
You may not have a formal “portfolio management” function within your data science team, but in all likelihood, you’re executing some of its key components already. But being more intentional around portfolio management can pay big dividends. Without it, you could be missing out on a powerful and holistic way of demonstrating the value your team provides to the business.In this episode, Katya Hall
How to Launch a Data Science Team Built for Scale (Mike Foley, Senior Director of Data Science, Hitachi Vantara)
Mike Foley has been building data science teams from scratch since before they were called “data science” teams. His perspective on questions like “Where do I start?” or “How do I get buy-in?” can help leaders growing data science teams of any size avoid some pitfalls along the way.Currently the Senior Director of Data Science at Hitachi Vantara, Mike joined Dave for a conversation that goes deep
Exploring the Future of Data: Regulations & Managing Analytics Teams (John Thompson, Global Head of Advanced Analytics & AI, CSL Behring)
Between GDPR, CCPA, and more regulatory frameworks on the horizon, the landscape of personal data—and how it can be used in business—is shifting.On this episode, John Thompson, Global Head of Advanced Analytics & AI at CSL Behring, joins host Dave Cole to discuss that shift, and a potential future in which we as individuals could be compensated for the use of our data.Plus, John shares the two typ
Data Challenges and the Promising Role of Product Analytics in Healthcare
In a perfect world, healthcare data would always be strategically organized, up-to-date, and easily accessible—all in a patient-centered, privacy-first way. But the reality is much more complex.Robin Foreman, Director of Data Science at CVS Health, joins the show to discuss the challenging world of data science in clinical trials. She also explains how product analytics can be used on the back end
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