Welcome to the official Data Science Salon Podcast!
Since its launch six years ago, our podcast has quickly become one of the top 10 machine learning and AI podcasts. Hosted by Q McCallum, our Senior Content Advisor and Anna Anisin, founder of the Data Science Salon, each episode dives deep into the world of data science, machine learning, and AI. Our guests range from DSS speakers to renowned authors and industry professionals, each bringing their unique insights and perspectives on trends and business use cases within these dynamic fields.
NEW – Episode FIFTY-EIGHT
Ethical AI and Data Science with Kelly Vincent
In this episode of the Data Science Salon Podcast, we sit down with Kelly Vincent, a data scientist at Hill’s Pet Nutrition and doctoral student at Purdue University focused on tech ethics. Kelly shares their journey from software engineering to data science, exploring the intersection of ethics, behavioral economics, and AI.
Kelly discusses how ethical considerations influence machine learning, NLP, and data quality, and how organizations can integrate human-centered thinking into technical decision-making. They also share insights from their upcoming book, The Friendly Guide to Data Science, aimed at making the field accessible, ethical, and practical.
Episode FIFTY-SEVEN
From Code to Scale: Building SaaS and AI Products That Deliver Value
In this episode of the Data Science Salon Podcast, we sit down with Swarnendu De, founder of AllRide Apps and Innofied Solutions, to discuss his journey from late nights debugging code to leading the architecture and delivery of 600+ scalable digital products. Swarnendu shares his experience building SaaS and AI platforms for startups and global enterprises, mentoring tech leaders, and integrating AI in ways that generate real business value.
He dives into frameworks like the SaaS Product Success Strategy™ and TechBlueprint Architecture Framework™, and shares insights on turning product ideas into execution-ready roadmaps, designing modular and scalable systems, and creating AI-powered business automation.
Episode FIFTY-SIX
Always-On Customer Care: How AI Agents Are Transforming Support
In this episode of the Data Science Salon Podcast, we sit down with Nitin Kumar, Director of Data Science at Marriott International, to discuss how AI agents are transforming customer support. Nitin shares his experience designing enterprise-scale AI and Generative AI solutions across 30 global brands, creating intelligent, proactive, and human-centered customer care systems.
He dives into AI-powered pipelines that monitor incoming emails, analyze sentiment and issues, and draft contextual responses for human agents to review. Beyond individual cases, these systems continuously feed real-time trend data, helping teams identify emerging issues before they become widespread.
Episode FIFTY-FIVE
Responsible AI and the Future of Machine Learning with Swati Tyagi
In this episode of the Data Science Salon Podcast, we sit down with Swati Tyagi, an AI/ML expert and responsible AI advocate. With deep expertise in large language models (LLMs), generative AI, and AI automation, Swati has led AI-driven innovation in FinTech, healthcare, and finance, helping organizations build scalable, ethical AI systems.
Currently at JPMorgan Chase, Swati’s work focuses on automating financial applications and leveraging LLMs for real-time inferencing. Her passion for responsible AI is central to her approach, ensuring that AI systems are not only powerful but also ethical and scalable.
Episode FIFTY-FOUR
Transforming the Workplace: Practical Strategies for Organizational Success with Melissa Swift
In this episode of the Data Science Salon Podcast, we sit down with Melissa Swift, Founder & CEO of Anthrome Insight, and expert in organizational transformation. With over a decade of experience, Melissa partners with organizations to tackle complex challenges using data analytics, pragmatism, and a humanist approach to leadership and workplace development. Melissa is also the author of “Work Here Now: Think Like a Human and Build a Powerhouse Workplace”, where she shares 90 actionable strategies for creating a workplace that fosters change, adapts to new demands, and builds resilient teams.
Episode FIFTY-THREE
Empowering Change: Neha Mehta’s Vision for FinTech, Sustainability & Financial Inclusion
In this episode of the Data Science Salon Podcast, we sit down with Neha Mehta, a globally recognized FinTech leader, AI expert, and sustainability advocate. As the Founder and CEO of FemTech Partners, Neha has spent over 19 years transforming the financial landscape, focusing on financial inclusion, women’s empowerment, and sustainable development. She is also the author of One Stop, a bestselling book that explores the potential of Super Apps in reshaping financial services for underserved populations.
In this conversation, Neha shares her journey from pioneering FinTech solutions to advancing Sustainable Development Goals (SDGs), her work in ClimateTech, and how AI can drive financial inclusivity. She also discusses her vision for the future of sustainable finance, her work with blue economy initiatives, and the impact of technology on climate action.
Episode FIFTY-TWO
Agentic AI and the Future of Compliance: Revolutionizing Decision-Making and Risk Management in FinTech
In this episode of the Data Science Salon Podcast, we sit down with Kalpan Dharamshi, VP at JP Morgan Chase, and a leader in Machine Learning and Cloud Architecture. Kalpan shares his journey from cloud architecture to AI-driven compliance solutions and how his work is transforming decision-making processes in the FinTech industry.
Kalpan’s focus on Agentic AI—autonomous systems that can handle compliance, risk management, and real-time decision-making—has reshaped the way financial institutions manage compliance. He discusses how large language models (LLMs) and AI agents can automate and scale compliance procedures, making them proactive, accurate, and cost-effective.
Episode FIFTY-ONE
Beyond the Model: Engineering Trust, Scale & Speed in AI-Powered Systems
In this episode of the Data Science Salon Podcast, we sit down with Anusha Nerella, a Senior Technology Leader | Global Fintech Industry. With over a decade of experience across top-tier institutions like Barclaycard, Citibank, and USPTO, Anusha brings deep technical expertise in AI/ML automation, enterprise engineering, and scalable financial systems.
In this conversation, Anusha shares her journey from software development to leading enterprise-scale AI initiatives, her work in high-frequency trading and automation frameworks, and her passion for mentoring and advancing the next generation of tech talent.
Episode FIFTY
Architecting AI-Driven Financial Systems: Innovation at the Intersection of Fintech and Emerging Tech
In this episode of the Data Science Salon Podcast, we sit down with Sasibhushan Rao Chanthati, AVP and Senior Software Engineer at T. Rowe Price, where he’s building the future of finance through intelligent, scalable technologies.
Sasibhushan walks us through the technical backbone of modern financial infrastructure and how AI is redefining intelligent automation.
Episode FORTY-NINE
Proactive by Design: How AI Predicts and Prevents Failures
In this episode of the Data Science Salon Podcast, we sit down with Vishnupriya Devarajulu, a Software Engineer specializing in AI- and ML-driven performance optimization for large-scale enterprise systems. With deep expertise in backend engineering, system diagnostics, and intelligent test automation, Priya is redefining how organizations build systems that don’t just respond—they anticipate.
Priya walks us through her work designing adaptive frameworks that use machine learning to forecast system bottlenecks, improve latency, and optimize performance in high-stakes environments like finance.
Episode FORTY-EIGHT
AI for Good: Innovating People-Centric Solutions
In this episode of the Data Science Salon Podcast, we are joined by Praveena Dhanalakota, the Founder & CEO of Soopra.ai, a San Francisco-based startup that is revolutionizing industries with AI-driven solutions. Praveena is an AI expert, tech evangelist, and a passionate advocate for using technology to address real-world challenges. In this episode, she shares her inspiring journey as an entrepreneur, her mission to solve people’s problems with AI, and her vision for the future of technology.
This episode is perfect for anyone interested in the future of AI, the startup ecosystem, or how technology can be harnessed to solve pressing human challenges.
Episode FORTY-SEVEN
AI-Driven Financial Modeling and Leading Diversity in Quantitative Analytics
In Episode 47 of the Data Science Salon Podcast, we’re joined by Akhil Khunger, the VP of Quantitative Analytics at Barclays. With over 10 years of experience in the financial industry, Akhil has a wealth of knowledge in statistical modeling, risk management, and AI-driven forecasting. He leads efforts in developing cutting-edge financial models and adapting the Basel IV framework for Risk Weighted Assets (RWA) models. Beyond his technical expertise, Akhil is also a strong advocate for diversity within his team, leading initiatives to foster inclusive and high-performance environments in Quantitative Analytics.
In this episode, Akhil shares his journey from stress testing to AI-driven forecasting and discusses how he integrates diversity into his leadership practices. He also reflects on the biggest trends shaping the future of finance and AI.
Episode FORTY-SIX
AI-Driven Retail – Transforming Operations with Innovation and Diversity
In Episode 46 of the Data Science Salon Podcast, we explore how AI is revolutionizing the retail industry, driving operational efficiencies, and fostering innovation and diversity. This episode dives into the intersection of AI, leadership, and business strategy, featuring a discussion on how AI is transforming the way retailers optimize operations and enhance customer experiences.
Our guest Angie Westbrock, CEO of Standard AI shares insights on:
Harnessing AI for Retail Transformation: Learn how AI and computer vision are reshaping retail operations, providing real-time insights to optimize business performance and streamline customer experiences.
Building Diverse, High-Performance Teams: Discover strategies for cultivating diverse teams that drive innovation, solve challenges, and create meaningful solutions in fast-paced industries.
Leading with Innovation: Explore how leadership in tech requires a blend of strategic thinking, operational excellence, and a strong commitment to fostering inclusive and forward-thinking company cultures.
Whether you’re interested in AI’s impact on retail or how to lead with diversity and innovation, this episode offers valuable perspectives for business leaders, AI practitioners, and anyone looking to understand the future of AI in business.
Episode FORTY-FIVE
Driving Business Impact with AI: A Conversation with Maddie Daianu of Credit Karma
Join us for Driving Business Impact with AI: A Conversation with Maddie Daianu of Credit Karma. In this episode of the Data Science Salon Podcast, host Anna Anisin sits down with Maddie Daianu, Head of Data & AI at Credit Karma and former executive at Meta, to explore how AI, machine learning, and data-driven strategy can fuel enterprise-wide transformation. With a proven track record of driving revenue growth and innovation through AI, Maddie shares her approach to aligning ML initiatives with business outcomes, scaling high-performing teams, and influencing executive stakeholders around data-led opportunities.
This conversation covers everything from monetization and predictive analytics to building a collaborative culture between technical and non-technical teams. Maddie also offers practical advice for data leaders navigating complex industries like fintech, and her perspective on the trends shaping the future of AI in business.
Whether you’re leading a data team or just beginning to build one, this episode offers actionable insights on harnessing the power of AI to drive meaningful impact at scale.
Tune in to gain leadership insights from one of the data industry’s most influential figures and learn how you can contribute to a more diverse and inclusive data science landscape.
Learn more about ML/AI in Finance at DSS NYC on May 15: https://www.datascience.salon/newyork/
NEW – Episode FORTY-FOUR
Beyond the Numbers: Leadership, Diversity, and Data
Join us on “Beyond the Numbers: Leadership, Diversity, and Data with Natalie Cramp, Partner at JMAN Group,” where we dive deep into the intersections of data science, leadership, and advocacy for diversity. Each episode, hosted by Natalie Cramp, offers an exploration of how data-driven strategies can reshape industries and enhance decision-making processes. Natalie brings nearly two decades of experience across private, public, and third sectors, providing unique insights into mobilizing technology and people to address complex challenges.
In this series, we’ll uncover the transformative power of data in driving business success and societal change. Natalie will share her expertise in scaling organizations, entering new markets, and leading significant transformations. Additionally, we focus on her passionate work in promoting gender equality in healthcare through data, offering listeners actionable insights and inspiration to leverage data for impactful change.
Whether you’re a CEO looking to harness the potential of AI, a data professional aiming to advance in the tech field, or someone interested in the crucial role of data ethics and education, this podcast will equip you with the knowledge and perspectives needed to lead effectively in today’s data-centric world.
Tune in to gain leadership insights from one of the data industry’s most influential figures and learn how you can contribute to a more diverse and inclusive data science landscape.
Learn more about Leadership in AI/ML at DSS SEA on April 16 https://www.datascience.salon/seattle/
Episode FORTY-THREE
Bridging AI and Business: Conversational AI & Communicating Data Value
In this episode of the Data Science Salon Podcast, host Anna Anisin sits down with two incredible leaders driving innovation in AI and data science.
First, Noelle Russell, CEO at AI Leadership Institute, shares her expertise on Conversational AI and intelligent contact centers. She discusses how companies can leverage AI-driven solutions to enhance customer experiences, streamline operations, and overcome key challenges in implementing intelligent engagement strategies. Noelle also highlights her experience leading AI initiatives at top tech companies, offering a unique perspective on the evolving role of AI in business.
Next, Amarita Natt, Managing Director of Data Science at Econ One Research, dives into one of the biggest challenges in data science: communicating the value of AI and ML projects to business leaders and clients. She explores the common disconnect between technical teams and executives, sharing strategies for framing data insights in a way that drives decision-making and measurable impact.
Both guests provide valuable takeaways for data professionals looking to bridge the gap between AI technology and real-world business success. Tune in for an engaging conversation on AI adoption, communication strategies, and the future of intelligent systems in business!
Episode FORTY-TWO
AI for Good: Generative AI’s Impact & Elevating Women in STEM
In this episode of the Data Science Salon Podcast, host Anna Anisin sits down with two powerhouse leaders shaping the future of AI and inclusivity in tech.
First, Jennetta George, SVP of AI at AlixPartners & CEO of Artificially Intelligent, shares her expertise on leveraging Generative AI for real-world impact. From forecasting market trends in finance to optimizing operations in healthcare and insurance, Jennetta dives into how LLMs are moving beyond hype into practical enterprise adoption. She also discusses strategies for navigating AI challenges and how businesses can harness AI for competitive advantage.
Next, Anna is joined by Eve Psalti, Principal Group Program Manager at Microsoft and a passionate advocate for women in STEM. Eve highlights the barriers women still face in tech and the steps needed to foster a more inclusive industry. She shares insights on mentorship, hiring practices, and the importance of diverse leadership in AI and data science.
Both guests provide invaluable perspectives on the evolving AI landscape and the role of diversity in driving innovation. Tune in to explore the intersection of AI, business transformation, and inclusivity in tech!
Episode FORTY-ONE
Building Data Excellence at Nordstrom: Scaling Standards & Measurement for Impact
In this episode of the Data Science Salon Podcast, host Anna Anisin sits down with two data leaders from Nordstrom to explore how organizations can build a culture of technical excellence and measurement in data science.
First, Gina Schmalzle, Principal Data Scientist at Nordstrom, shares her experience leading the Technical Excellence Initiative within the company’s data science and analytics organization. She discusses the challenges of scaling data teams, the importance of setting standards for efficiency and collaboration, and how MLOps and feature stores can streamline data science workflows. Gina provides practical insights into creating high-quality, scalable data solutions that drive business impact.
Next, Kevin Haynes, former Program Manager at Nordstrom, takes us into the world of “Eating Your Own Dog Food”—Building a Culture of Measurement for Data Products. He explores why internal metrics are essential for validating and improving data-driven solutions and how data teams can adopt a product mindset when developing internal tools. Kevin also shares his approach to fostering an engaging, high-impact team culture while ensuring that measurement and accountability remain at the core of data initiatives.
Both guests offer interesting insights into building sustainable, high-performing data organizations in today’s evolving AI and data landscape. Tune in to learn actionable strategies from two data leaders shaping the future of AI and analytics.
Episode FORTY
Exploring the Past, Present, and Future of AI/ML
In this episode of the Data Science Salon Podcast, host Anna Anisin sits down with two influential leaders in AI and data science to discuss their experiences, challenges, and insights into the evolving landscape of the industry.
First, Fatma Tarlaci, Chief Technology Officer at Rastegar Capital, shares her journey as an AI engineering leader, discussing the intersection of technical execution and strategic leadership. She explores the importance of responsible AI, open-source contributions, and aligning technical teams with business goals to drive impactful solutions. Fatma provides actionable insights on fostering innovation while maintaining ethical AI development.
Next, Brent Schneeman, Director of AI and Software Engineering at PMG, brings his unique perspective on building high-performing interdisciplinary teams and navigating the evolving expectations in AI and machine learning. He shares lessons learned from his journey, insights into stakeholder collaboration, and the importance of cultivating a “test and learn” culture within organizations.
Both guests provide invaluable perspectives on leading AI initiatives, overcoming industry challenges, and staying ahead in an era of rapid technological change. Tune in to gain practical knowledge and inspiration from their experiences.
Episode Thirty Nine
2025 Predictions: The Future of AI, LLMs, and Data Science
In this episode, Anna Anisin, Founder of Data Science Salon, and Tyler Carmody, Head of Event Operations, catch up on everything we missed over the past few weeks. They dive into exciting developments in AI, including how it’s transforming scientific research, solving complex problems, and revolutionizing business tools. They also discuss predictions for 2025—what trends we expect to see in AI, LLMs, and generative AI, and how these technologies are shaping industries across the globe.
Plus, don’t miss exciting news about the upcoming DSS ATX event on February 19-20, with a special discount code DSSPODCASTATX for 20% off your registration. We’re also looking for startups to join our showcase—check the application link in the description!
Tune in for insights and trends you won’t want to miss as we head into the new year!
Episode Thirty Eight
Data-Driven Excellence: AI and Analytics in Action with Matthew Denesuk & Jaime Russ
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, focusing on integrating advanced analytics and machine learning models into traditionally held concepts. Tune in as she explores the application of machine learning in corporate finance and its fascinating parallels to fleet management.
Episode Thirty Seven
AI in Action: From Machine Learning Interpretability to Cybersecurity with Serg Masís and Nirmal Budhathoki
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 scientists striving to create more transparent and effective AI solutions.
In another compelling episode, Anna sits down with Nirmal Budhathoki, Senior Data Scientist at Microsoft. Nirmal, who has extensive experience at VMware Carbon Black and Wells Fargo, focuses on the intersection of AI and cybersecurity. He shares his journey into security data science, discussing the unique challenges and critical importance of applying AI to enhance cybersecurity measures. Nirmal highlights the pressing need for AI in this field, practical use cases, and the complexities involved in integrating AI with security practices, offering a valuable perspective for professionals navigating this dynamic landscape.
Episode Thirty Six
AI at the Crossroads: Bias, Diversity, and Scalability with Boshika Tara and Dr. June Andrews
In this week’s DSS Podcast, 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 representation to mitigate these biases.
Additionally, Anna had the pleasure of hosting Dr. June Andrews, the Founder of Lat Long Labs. Dr. Andrews shares her incredible journey from leading the Style Discovery team at Stitch Fix to her role as a Tech Lead at LinkedIn. She discusses the complexities of scaling and transforming AI projects, particularly in predicting consumer preferences and enhancing product discovery.
Episode Thirty five
Elevating Computer Vision and Female Voices with Alex Levinson and Sheila Beladinejad
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 the field and highlights an exciting trend in AI that she’s currently following.
Next, Anna introduces Sheila Beladinejad, President of Women in AI & Robotics. Sheila talks about the network she built in Germany, dedicated to fostering gender-inclusive, ethical, and responsible AI and robotics solutions. She highlights the importance of creating such a network and the positive impact it has had on the AI and robotics community.
Episode Thirty four
USING AI & MACHINE LEARNING TO DEVELOP BETTER HEALTHCARE EXPERIENCES WITH SUMAYAH RAHMAN AND VAIBHAV VERDHAN
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 the transformative impact of AI/ML in healthcare.
Next, Vaibhav Verdhan, Analytics Leader at AstraZeneca, dives into the role of computer vision in healthcare and his favorite technologies in the healthcare analytics space. He discusses how advanced analytics are driving innovation at AstraZeneca by developing, deploying, and maintaining decision support capabilities. Both guests provide valuable insights into how AI and ML are revolutionizing healthcare, offering listeners practical knowledge and inspiration.
Episode Thirty three
LESSONS LEARNED FROM APPLYING DATA SCIENCE IN FINANCE AND A DEEP DIVE INTO DRIFT WITH MABU MANAILENG AND ADAM LIEBERMAN
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, discusses statistical measures to quantify it, and provides strategies for maintaining model health, ensuring that models continue to serve users’ needs effectively.
Episode Thirty two
Leveraging Statistical Models and ESG to Grow Your Business with Laura Gabrysiak and Rochelle March
In this episode, Anna sits down with two leaders in the finance industry, exploring the forefront of AI, ML, and ESG innovations.
First, let’s welcome Laura Gabrysiak, Data Science Leader at Visa. Laura develops statistical models and decision analytics tools that enable Visa clients to transform massive amounts of data into actionable ML models and AI implementations. She’s also passionate about fostering the local data science community in Miami as the Founder of R-Ladies Miami. In this conversation, they dive into the future of ML/AI in financial services and the impactful work being done with Code Art to promote diversity in tech.
Next, we have Rochelle March, former Head of ESG Product at Dun & Bradstreet. Rochelle specializes in impact analysis related to carbon, water, and the Sustainable Development Goals, and applies machine learning to ESG products. She also teaches data and analytics at Bard College’s MBA program, sits on the advisory board for USL Technology, Inc., and mentors fellows in the Environmental Defense Fund’s Climate Corps program. Since recording this episode, Rochelle has started her own company, People Places Words Actions. In our discussion, we explore her journey in ESG innovation and analytics, why ESG data is crucial for responsible investment decisions, and how it drives sustainable business practices.
Tune in to learn from these industry thought leaders and gain insights into the cutting-edge applications of AI and ESG data in the finance sector.
Episode Thirty one
FinTech Insights: AI Innovations, Privacy Strategies, and Synthetic Data with Harry Mendell & Supreet Kaur
Episode Thirty
Context Matters: Generative AI, the spectrum of worldviews, and understanding propaganda’s appeal
Episode Twenty Nine
When companies try to “sprinkle some AI” on a product
If you’ve been in the data game long enough, you’ve probably seen this before: a stakeholder or product owner approaches you with a project that’s 95% done, and they’d like you to … “sprinkle some AI on it.” They’ve heard that this “AI” thing can be useful so they want some of it in their latest effort.
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?”
Ultimately, the pair work through the bigger issue: how do you make peace with companies throwing money at AI like this? And how can these companies use this approach to their advantage?
As a bonus, Noelle shares how she made the move from a data scientist role into product management. If this path sounds interesting to you, take a listen.
Episode Twenty Eight
Building data products with Solomon Kahn
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 learned a lot and we’re excited for him to share some of that hard-earned knowledge here on the show.
In this extended conversation, the two explore: the reasons why building a data product is different (and, in many ways, more difficult) than building traditional software products; how the people involved can impact the outcome; why a good sense of risk management can make all the difference; and what purple cars have to do with all of this. (No, seriously. Purple cars.)
Along the way, the pair talk about the early days of the data field, and how much it has changed.
Episode Twenty Seven
Probabilistic Thinking with James “JD” Long
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” who does a lot of work in R, Python, and AWS. Through his work in the reinsurance field he has developed deep knowledge of simulations and probabilistic thinking, as well as an ability to explain these topics in plain language.
Episode Twenty Six
The roles of economists in data science, with Dr. Amar Natt
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 in others. From there, she tells us about techniques economists can learn from data scientists, and what data scientists can pick up from econ. (Hint: “causal inference.” You heard it here first.)
Episode Twenty Five
ML at The Home Depot with Pat Woowong: The Falloff Model and Lead Scoring
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 inside the business. To frame this, he walked me through the Falloff model and Lead scoring, two projects that his team deployed to address the unique challenges of a company that handles both retail and services.
During our conversation, we discussed: understanding where models fit into the bigger business picture; using expert domain knowledge to drive feature selection and feature engineering; the value of process; and, to top it off, what it’s like to work at The Home Depot.
Episode Twenty Four
Coffee Chat: Inspiring ML Use Cases in Retail Delivering Measurable Impact
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 wide.
Episode Twenty Three
Data Science and Data Engineering in the Federal Space with Dr. Pragyansmita Nayak
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 you can’t rely on metrics like “profit.” And, the big question: should we release t-shirts that read “just give me my AI solution!” ?
You can find Pragyan online:
Twitter: https://twitter.com/SorishaPragyan
LinkedIn: http://linkedin.com/in/pragyansmita
The book Q mentioned is Army of None, by Paul Scharre.
EPISODE TWENTY TWO
SOFTWARE DEVELOPMENT SKILLS IN ML/AI
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? Listen to Murium and Q explore topics such as writing tests, using Docker to isolate dependencies, and learning best practices from your software developer teammates.
Episode Twenty One
COFFEE CHAT: MODEL INTERPRETABILITY AND HOW TO CREATE TRUST IN AI PRODUCTS
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 model interpretability and how to create trust in AI products.
Episode Twenty
Coffee Chat: DSS Hybrid Miami 2022
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.
Charles Irizarry, CEO & Co-Founder at Strata.ai had the chance to talk to Nirmal Budhathoki, Senior Data Scientist at VMware Carbon Black and Moody Hadi, Group Manager – New Product Development & Financial Engineering at S&P Global. Tune in to hear about ML techniques they are using in their current roles, tools to put ML into production, model explainability, and future trends.
Episode Nineteen
Communal Computing and AI with Chris Butler – Pt. 2
Episode Eighteen
Coffee Chat: DSS Virtual 2021/12: Applying AI & Machine Learning to Finance & Technology
This episode is a recording from our recent Data Science Salon event, which focused on applying AI and ML to finance and technology. Our Senior Content Advisor Q McCallum sat down with data scientists Linda Liu (Hyrecar) and Giacomo Vianello (Cape Analytics) to talk about their work. We explored the techniques and tools for the various data projects they’re running, some of the challenges of working with geospatial data, and how they approach R&D efforts in the company. (The hint for that last one: balance, discipline, and structure rule the day. Very practical.)
Episode Seventeen
AI, Product, and Uncertainty with Chris Butler – Pt. 1
Episode Sixteen
Coffee Chat: DSSe Virtual 2021
Episode Fifteen
Analytics vs. Data Science vs. ML Research: Economist Sonali Syngal Shares Her View
Episode Fourteen
Charting a Course: from Physics PhD to Professional Data Scientist with Dr Resham Sarkar
Episode Thirteen
Data Monetization Strategies with Micheline Casey
Episode Twelve
Software Testing, Performance Tuning, and Code Handoff for Data Scientists
Episode Eleven
Coffee Chat at DSSVirtual for Healthcare, Finance & Technology
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.
Episode Ten
Trading, Risk, and Reinsurance with Otakar Hubschmann
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. Along the way, Otakar offers his favorite tips for hiring data scientists. (Whether you’re applying for a job, or hiring for one, take note.)
Episode Nine
Virtual Coffee Chat: Live from DSS Virtual
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:
Thulasi Nambiar – Senior Manager, Marketing Data Science at Prosper, Jeff Sharpe – Senior Manager / Tech Lead at CapitalOne, Sonali Syngal – Applied Scientist and Project Lead AI Garage at Mastercard
Episode Eight
Virtual Coffee Chat: Live from DSS Virtual
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.
Phillip Rossi, Head of Data Science at Shopify, Laya Shamgah, Data Scientist at Lowe’s Company, Jeffrey Yau, Head of Data Science at Walmart Labs, Samantha Cvetkovski, Data Science Manager at Mindbody
Episode Seven
Automated Content Moderation and the Intersection of AI and Law
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. He’s worked for a couple of law firms that you may have heard of, and for a tech company that you have most certainly heard of.
Shane gave us an attorney’s view on AI practices, explored the ways in which an attorney can help with an AI effort, and explained the how, when, and why AI teams should involve their legal counsel. (Hint: early. Very early.) Shane also talked about the legal and technical aspects of AI-driven, automated content moderation.
At the end of the episode, Shane mentions some blog posts that Q wrote on AI lessons learned from the world of algorithmic trading. That series starts here.
Episode Six
Virtual Coffee Chat: Live from DSS Virtual
We recorded this episode at our September 2020 Data Science Salon virtual event on Media, Advertising, & Entertainment. Formulatedby’s Senior Content Advisor, Q McCallum, sat down with some new friends to discuss trends and challenges in the world of AI:
Anne Bauer – Director of Data Science at The New York Times, Yves Bergquist – Director of the AI & Neuroscience in Media Project, at USC, Kim Martin – Engineering Leader of Data Science and Engineering at Netflix, Dominick Rocco – Data Scientist at phData
Episode Five
Mission and Purpose in Data Science: Lessons from the Military and Intelligence
How can mission and purpose drive a data professional? And what happens when we can no longer trust the data that’s presented to us?
Richard Dunks served as a member of the US Army and the intelligence community (IC), where he honed skills that he now uses in his civilian pursuits as a data scientist, trainer, and educator. He recently caught up with Q McCallum (Senior Content Advisor at Formulatedby, the company behind Data Science Salon) to talk about what his time in the IC taught him about data analysis, having a sense of mission, and what it means to lose trust in data.
Episode Four
Marcello La Rocca on Algorithms and Data Structures
The term “algorithms” has several meanings, from machine learning models to tools of Wall St traders. Then there’s the classic computer science definition: a set of instructions for solving problems. Think “simulated annealing,” “evolutionary computing,” or “LRU cache.” These are the sort of algorithms we’ll explore today.
Episode Three
Jean-Georges Perrin on Spark and Data Quality
Our guest for this episode is Jean-Georges Perrin, the author of Spark in Action, 2nd edition. We talk about his career path (he’s been doing “big data” since before the term existed), what inspired him to write Spark in Action, and where Spark fits in your company’s data efforts. He also shares his thoughts on data quality.
Episode Two
Applications of Data Science in Media & Entertainment
The Media and Entertainment industry has undeniably been heavily disrupted by changes in technology. Listen as Ayan Battacharya, Advanced Analytics Specialist Leader at Deloitte Consulting and Harini Krishnan, Data Scientist at Capsule8, share observations they’ve garnered from their own experience on the state of data science in Media & Entertainment, live from DSS NYC 2019.
Episode ONE
Prolific vs. private data in media advertising @ DSS NYC
In June 2019, over 200 data scientists gathered at Viacom HQ in New York to hear key industry players’ takes on what makes an effective data-driven strategy. Q McCallum, Senior Content Adviser at Formulated.by, took a deeper dive into the major topics of concern for data science when he spoke with DSS NYC speakers Lauren Lombardo, Senior Data Scientist at Nielsen and Sergey Fogelson, Vice President of Data Science and Modeling at Viacom. Listen as they speak about current practices and debate the ways in which the growth of AI will impact advertising.
