In this DSS Podcast we chat with Matthew Denesuk, SVP of Data Analytics & AI at Royal Caribbean Group. Matthew shares his insights on leveraging a Center of Excellence model to drive data-driven strategies across the organization. Tune in to discover how this approach can transform enterprise business processes using AI, analytics, and data science! We’re also excited to welcome Jaime Russ, former Principal Data Scientist at Ryder System. Jaime brings a fresh perspective on data science,...

In this DSS Podcast, Anna Anisin welcomes Serg Masís, Climate and Agronomic Data Scientist at Syngenta. Serg, an expert in machine learning interpretability and responsible AI, shares his diverse background and journey into data science. He discusses the challenges of building fair and reliable ML models, emphasizing the importance of interpretability and trust in AI. Serg also talks into his latest book, "Interpretable Machine Learning with Python," and provides valuable insights for data...

In this week's DSSPodcast, Anna had a conversation with Boshika Tara, Technical Machine Learning Product Manager at H&M Group. Boshika brings over 7 years of experience in technical product development, engineering, and building large-scale ML systems in NLP and Computer Vision. In this episode, she dives into the critical issue of bias in AI, discussing various types of biases in machine learning, how to detect them, and the importance of creating more equitable teams with diverse...

In this episode of the DSS Podcast, Anna Anisin introduces two powerhouse guests in the realms of AI and robotics. First, Anna welcomes Alex, Principal Algorithms/AI Engineer at Elbit Systems of America, based in Miami. Alex shares her journey into the field of AI, particularly computer vision, and discusses common use cases, pitfalls, and success stories in sourcing and improving data for computer vision models. She also offers valuable recommendations for data scientists starting out in...

In this episode of the Data Science Salon Podcast, host Anna Anisin sits down with two leading experts in the ML/AI healthcare industry. First, Sumayah Rahman, Director of Data Science - Machine Learning and Infrastructure at Cedar, discusses optimizing the patient experience to make healthcare more affordable and accessible. She explains how ML-powered discounts can benefit both patients and providers, sharing practical examples of using data to enhance patient experiences and highlighting...

In this episode, Anna sits down with two leaders in the finance industry, exploring the forefront of AI and ML innovations. First, we have Mabu Manaileng, Lead Data Scientist at Standard Bank Group. Mabu shares his journey and current role, highlights the challenges of applied data science in the financial sector, and discusses the transformative impact of AI on banking in the coming years. Next, we welcome Adam Lieberman, Head of AI and ML at Finastra. Adam defines the concept of drift,...

In this episode, Anna sits down with two distinguished leaders in the ML/AI finance industry. First, we have Harry Mendell, Technology Group Data Architect at the Federal Reserve Bank of New York, who brings over 30 years of expertise in FinTech. Harry shares compelling stories and discusses emerging trends in the finance sector. Following Harry, Supreet Kaur, AVP at Morgan Stanley and product owner for various AI products, joins the conversation. Supreet provides insights into the use of...

Ben Dubow of Omelas joins us to talk about data in context, NLP/NER at scale, and the impact of generative AI on democracy + authoritarianism.

Data scientist-turned-product person Noelle Saldana has experienced the "sprinkle some AI on it" request more times than she'd care to remember. Our Senior Content Advisor Q McCallum met up with Noelle to explore this phenomenon. How does this happen? (Hint: "corporate FOMO.") What should you do when stakeholders insist on implementing AI that isn't actually going to help? What about when your data scientist peers seem like they're doing this for the sake of "résumé-driven development?"

Sometimes the most valuable data IN your company ... is the data LEAVING your company. That's Solomon Kahn's view on data products, as well as the premise behind his latest venture: Delivery Layer. For this episode, our Senior Content Advisor Q McCallum reached out to Solomon to check in on the new startup, and to tap his expertise in the world of data products. Solomon's been at this a while. He's run high-revenue data products in some notable places, including Nielsen. Over the years he's...

Our show host and Senior Content Advisor, Q McCallum, has been thinking a lot about what he calls "moving beyond the point estimate" in ML modeling. That usually starts with seeing the world in terms of statistical distributions, and running simulations to get a more robust picture of a model's results. When he had questions, he reached out to his old friend James "JD" Long for answers. James is a self-described "agricultural economist, quant, stochastic modeler, and cocktail party host"...

We've all heard the term "economist," sure. But exactly what does and economist do? And as economics is a very data-driven field, where does their work intersect with data science, machine learning, and AI? To answer that question, Senior Content Advisor Q McCallum spoke with Amar Natt, PhD. She's an economist at Econ One Research, and her work focuses on advanced analytics and predictive modeling. Does that sound like ML to you? Well, Amar explains that it's similar in some ways, different...

When people think about The Home Depot, they probably think more about lumber and tile than they do ML models. Sure, there is plenty of lumber. But machine learning also plays a key role in the business, in places that customers can see as well as the behind-the-scenes operations. Senior Content Advisor Q McCallum met up with Pat Woowong, Director of Data Science at The Home Depot, to explore how the company mixes their very rich dataset with domain knowledge to employ machine learning deep...

This episode is a coffee chat recording from DSS Virtual in May 2022. Charles Irizarry (Phygital) and Ankita Mangal (P&G) share in war stories of ML use cases they use in retail and eCommerce scenarios, brokering data, and protecting the important principles of data ethics and privacy. Ankita shares the digital transformation journey that P&G undertook, her growth together with P&G, and some of the incredible technologies P&G has developed to better serve their customers world...

A lot of data scientists work in the private sector: finance, adtech, retail, and all that. Today's guest offers her perspective on what it means to do data work in the federal space. In this conversation, our Senior Content Advisor Q McCallum spoke with Dr. Pragyansmita Nayak, Chief Data Scientist at Hitachi Vantara Federal. They explored how different federal agencies use data and how they share datasets with each other. They also talked about how to measure operational efficiency, when...

In this episode, our Senior Content Advisor Q McCallum met up with Murium Iqbal from Etsy. They spoke about an important skill for data scientists: software development! Data scientists write a lot of code, sure, but few of them come from a formal software dev background. That can lead them to struggle with slow, buggy code that ultimately holds back the company's ML efforts. Want to write cleaner, more performant code? Looking for ways to make those model deployments more reproducible? ...

This episode is a recording of the panel conversation at the virtual Data Science Salon in April 2022, which focused on AI & machine learning applications in the enterprise. Charles Irizarry (CEO & Co-Founder at Strata.ai) had the chance to talk to Amarita Natt (Managing Director, Data Science at Econ One Research), Preethi Raghavan (VP, Data Science Practice Lead at Fidelity Investments) and Serg Masís (Climate and Agronomic Data Scientist at Syngenta) about the important topic of...

This episode is a recording of the coffee chat at the hybrid Data Science Salon Miami, which focused on AI & machine learning applications in the enterprise.

In the previous episode, our Senior Content Advisor Q McCallum met with product manager Chris Butler to explore the role of uncertainty and how it relates to AI product management. That conversation sets the stage for Chris and Q to talk about communal computing today.

Today’s episode is a recording of the Coffee Chat from our Data Science Salon Virtual Finance & Technology. The Data Science Salon for Finance and Technology is the only industry conference that brings together specialists in the finance and technology data science fields to educate each other, illuminate best practices, and innovate new solutions in a casual atmosphere.

Welcome to our first two-part episode! Our Senior Content Advisor, Q McCallum, caught up with product manager Chris Butler to talk about the intersection of AI and product. In particular, Chris’s two decades of professional experience have taught him a lot about the role of uncertainty: we dig deep into what that term really means, how much data scientists need to concern themselves with uncertainty in their work, and how this relates to a company’s values.

Today’s episode is a recording of the Coffee Chat from our Data Science Salon Elevate series. Elevate is our unique women focused virtual conference that includes BIPOC, members of the LGBTQIA+, and other underrepresented groups.

The world of data has a lot of hazy definitions. This leads to confusion as people use the same terms in a conversation but mean very different things. Three such terms that are often conflated are "analytics," "data science," and "machine learning research." How do we tell the difference between them? And what are the different duties and qualifications of these roles?