Hosted by Domino Data Labs · 🇺🇸 US · EN · 48 episodes
Established thought leaders with verified media credentials.
Data science is booming, but scaling it in the enterprise is hard. The playbook is still being written. Data Science Leaders is a podcast for data science teams that are pushing the limits of what machine learning models can do at the world’s most impactful companies. Each episode features an interview with a leader in data science. We’ll discuss how to build and enable data science teams, create scalable processes, collaborate cross-functionally, communicate with business stakeholders, and more. Our conversations will be full of real stories, breakthrough strategies, and critical insights—all data points to build your own model of enterprise data science success. Data Science Leaders is hosted by Dave Cole.
Domino Data Labs hosts Data Science Leaders, a business show with 48 episodes published.
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
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
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 pro
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 succ
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
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 sc
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
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 opportuni
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
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
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 en
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 unders
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 negat
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-pro
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 o
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
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
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 f
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 predicti
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 ve
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Data Science Leaders is hosted by Domino Data Labs. The show is categorised under Business (Management) and has published 48 episodes.
Data Science Leaders has published 48 episodes.
Data Science Leaders regularly covers Business, Management, Science, Mathematics. It sits in the Business category, with a Management focus.
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Episodes of Data Science Leaders average 33 minutes. a focused format where a clear narrative arc and tight preparation matter most.
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