Data Science Leaders

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 give a glimpse of how it will affect the business landscape of tomorrow.

Join us as we discuss:

• Separate generative AI facts and fiction
• Take a closer look at AI applications you can start using today
• Examine the future of AI and its impacts on the workforce and the workplace

“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-in from the very top of the organization, and a multi-party effort in building and maintaining AI ethical risk programs.

Join us as we discuss:

• Why AI poses greater ethical risks than other technologies (and humans)
• Leadership and the other key elements of a successful AI / digital ethics program
• The importance of explainability

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 capability for data science?

In this episode, Alek Liskov, Director of AI & Data Product Management at Verizon, shares their hard-won best practices in building data science product teams and their phenomenal successes in delivering AI-driven impact.
Join us as we discuss:

• The emerging discipline of data science product management
• How to build durable product teams for data science
• Where to find and how to develop data science product managers

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 us to where we are today.

Join us as we discuss:

• A brief history of AI - from dashed hopes to triumphant transformers
• How AI is helping us understand human intelligence
• The regulatory risks of anthropomorphizing AI

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 leader, the experimental foundation of data science, the importance of data science leaders being a part of strategic conversations, and the hard-won best practices that have emerged. They also touch on the sales and marketing aspects of being a data science leader, and the evolving future of data science, and the data science leader.

Join as we discuss:

• The unexpected origins of data science leaders
• The emerging consensus on how to drive impact with data science
• How and why data science is moving higher and higher in organizations
• The future outlook for data science, and its leaders

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 data at any given moment, Walmart offers some unique lessons in the complexities of building teams, processes, and products to effectively leverage AI at scale.
In this episode, Srujana shares a few of those lessons, along with her perspective on nonlinear career paths, organizational collaboration and alignment, and her ongoing fascination with what’s next. Plus, she dives into her passion for fostering diversity in data science and tech, sharing strategies leaders can implement to help bring more women into the field.
We discuss:
What to prioritize when experimenting with next-gen tech
How to use “communities of practice” to align your organization
Solving governance, reproducibility, and knowledge sharing challenges at scale
Bringing more women into data science 


In this season finale episode, host Dave Cole also shares his three biggest takeaways from his many in-depth conversations with leaders in data science.
Stay tuned for a whole new season of Data Science Leaders coming soon! We're just getting started.
Tune in on Apple Podcasts, Spotify, our website, or wherever you listen to podcasts.
Can’t see the links above? Just visit domino.buzz/podcast for helpful links from each episode.

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 data at any given moment, Walmart offers some unique lessons in the complexities of building teams, processes, and products to effectively leverage AI at scale.

In this episode, Srujana shares a few of those lessons, along with her perspective on nonlinear career paths, organizational collaboration and alignment, and her ongoing fascination with what’s next. Plus, she dives into her passion for fostering diversity in data science and tech, sharing strategies leaders can implement to help bring more women into the field.

We discuss:

What to prioritize when experimenting with next-gen tech

How to use “communities of practice” to align your organization

Solving governance, reproducibility, and knowledge sharing challenges at scale

Bringing more women into data science

Tune in on Apple Podcasts, Spotify, our website, or wherever you listen to podcasts.

Can’t see the links above? Just visit domino.buzz/podcast for helpful links from each episode.

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 leadership has given him years of perspective on how ML professionals and their business side counterparts can build partnerships that pay off in both the near and long term.
In this episode, Sunil shares some of those key lessons on education, communication, and collaboration. Plus, he details a unique MLOps strategy he’s employed to address challenges with scaling model monitoring.
We discuss:
How a research background can inform leadership style
MLOps best practices for scale
Forming mutually beneficial partnerships between business stakeholders and data science teams



Tune in on Apple Podcasts, Spotify, our website, or wherever you listen to podcasts.
Can’t see the links above? Just visit domino.buzz/podcast for helpful links from each episode.

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 data and analytics functions at multiple organizations, and she knows a thing or two about negotiating the complexities of change management during analytics transformations.
In this episode, Michal shares her advice for AI leaders driving meaningful change at their own companies. Plus she details her philosophy on structuring data and analytics teams for maximum efficiency and collaboration.
We discuss:
Using experience in fields like accounting as building blocks for leadership in data science
Change management during model-driven transformations
A structure to enable BI and data science functions to better support each other 


Tune in on Apple Podcasts, Spotify, our website, or wherever you listen to podcasts.
Can’t see the links above? Just visit domino.buzz/podcast for helpful links from each episode.

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 path to model deployment. He shares how this hybrid approach enables his team to be more strategic about project lifecycles, unlocking real business impact even faster. 
Plus, David provides advice for building relationships with key business stakeholders and shares his philosophy on using the art of data science to benefit humanity. 
We discuss:
Implementing hybrid CRISP-DM and agile methodologies
Building relationships with stakeholders across the business
Using data science to solve challenges outside of work      


Mentioned during the show:
DataKind     


Tune in on Apple Podcasts, Spotify, our website, or wherever you listen to podcasts. 
Can’t see the links above? Just visit domino.buzz/podcast for helpful links from each episode.