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?

There's no single path to a data scientist role. Practitioners come from fields as varied as software development, economics, and academia. Many people in that last group aren't sure what it's like to transition from an advanced degree program into industry. That's why I was happy to speak with Dr Resham Sarkar, a machine learning expert who heads up personalization at Slice. Before she started building ML around pizza, she completed a PhD in physics and then worked in insuretech.

The idea of turning data into money has been a draw since the early days of the term "Big Data." As many companies have learned, sometimes the hard way, this isn't always easy and it's hardly guaranteed to work. That's where today's guest comes in. For this episode, Formulatedby's Senior Content Advisor Q McCallum sat down with Micheline Casey to explore the what, why, and how of a company monetizing its data. There are a lot of matters to consider, ranging from technology to policy to...

Data scientists and ML engineers write a lot of code: building data pipelines, wiring up models, and sometimes translating concepts from research papers into algorithms.

We recorded this episode at our February 2021 Data Science Salon Virtual on Healthcare, Finance & Technology. Formulated.by’s Senior Content Advisor, Q McCallum, sat down with Ayda Farhadi, Senior Data Scientist at UPS, and Vasileios Stathias, Lead Data Scientist at Sylvester Comprehensive Cancer Center to discuss applying AI to healthcare.

Our Senior Content Advisor Q McCallum sat down with Otakar Hubschmann, Head of Applied Data at TransRe, to talk about ML/AI in the world of reinsurance.  They take a deep dive into the insurance industry and the role reinsurance plays there, with a side-trip to show how this differs from the quantitative finance you see in hedge funds.

We recorded this episode at our December 2020 Data Science Salon Virtual on Finance & Technology. Formulated.by’s Senior Content Advisor, Q McCallum, sat down with some new friends to discuss trends and challenges in the world of AI.

We recorded this episode at our November 2020 Virtual Data Science Salon on Retail & Ecommerce. Formulated.by’s Content Advisor, Roger Magoulas, sat down with some of the event's speakers to talk about data science trends and challenges in retail & ecommerce.

Today's podcast is about the intersection of AI and the law. Formulatedby's Senior Content Advisor, Q McCallum, spoke with Shane Glynn, an attorney who has deep knowledge of the tech and AI worlds.