Next up on #DSSBreak — we're excited to welcome Ahsaas Bajaj, Senior Machine Learning Engineer II at Instacart and applied AI researcher recognized for building large-scale recommendation, retrieval, and personalization systems deployed in production!

In this episode of the Data Science Salon Podcast, we sit down with Dushyanth Sekhar, Head of AI & Data Platforms – Enterprise Data Organization at S&P Global – an AI and ML expert with experience designing and deploying scalable, production-ready AI systems across the enterprise. Dushyanth shares his journey into AI, the challenges of building complex pipelines, and how to integrate responsible and ethical practices into machine learning workflows. Key Highlights: • Scaling AI Systems: How to design and deploy pipelines that handle real-time inference, multimodal data, and production-level demands. • Model Interpretability & Explainability: Strategies for making complex models understandable and accountable. • Optimizing AI for Real-World Impact: Balancing performance, robustness, and human oversight in AI systems. • Responsible AI Practices: Embedding ethics, fairness, and transparency in machine learning workflows. 🎧 Tune in to Episode 61 to hear Dushyanth Sekhar’s insights on bridging technical innovation with responsible AI practices, and learn how to build AI systems that deliver both accuracy and real-world value. Be sure to mark your calendars for the 9th annual DSS ATX on Feb 18, where we will focus on GENAI AND INTELLIGENT AGENTS IN THE ENTERPRISE. Join us to hear from experts on how AI is shaping the future of the enterprise. https://www.datascience.salon/austin/

Architecting Agentic AI, Infrastructure, Evaluation & Real-Time Decisioning

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. Key Highlights: • AI Agents in Customer Support: Learn how AI agents automate routine processes while empowering human agents to focus on complex interactions. • Human-in-the-Loop Design: Explore strategies for balancing AI efficiency with human oversight and empathy. • Scaling AI Solutions: Insights into LLM integration, prompt engineering, and global deployment of enterprise AI systems. 🎧 Tune in to Episode 56 to hear how Nitin Kumar is revolutionizing customer support with AI agents and Generative AI to create more efficient, empathetic, and scalable systems. Be sure to mark your calendars for the 3rd annual DSS SF on Nov 6 [FREE!] thanks to our amazing sponsors, where we will focus on GENAI AND INTELLIGENT AGENTS IN THE ENTERPRISE. Join us to hear from experts on how AI is shaping the future of the enterprise. https://www.datascience.salon/san-francisco/

Scaling AI Responsibly: DataOps in the Era of Democratized Data Science

From Tokens to Trust: Building AI-Driven Loyalty at Scale

Driving Business Performance Through Data Science & Experimentation

Meet Mrunal Gangrade, VP of Data and Gen AI at JPMorgan Chase, where she’s bridging the worlds of healthcare, cybersecurity, and finance through ethical, data-driven innovation. From deploying machine learning in clinical environments to designing responsible AI systems at enterprise scale, Mrunal’s work is a masterclass in how data science can serve real human needs—while navigating complex systems and regulations. We’ll chat about: – How to apply AI ethically in healthcare – What cross-functional collaboration actually looks like – The biggest risks (and opportunities) in GenAI – How she’s thinking about bias, privacy & resilience in intelligent systems Don’t miss this one. Catch her live at #DSSMIA on September 17! #EthicalAI #WomenInData #MachineLearning

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. Key Highlights: • Workplace Transformation: Learn how data analytics and humanist leadership principles are used to unlock extraordinary outcomes in the workplace. • Practical Strategies for Success: Melissa discusses 90 strategies from her book, focusing on the skills and behaviors organizations need to thrive in a changing work environment. • Solving Wicked Problems: Melissa shares how she’s helped organizations tackle complex challenges and create lasting change. • Leadership in the Future of Work: What makes a great leader in today’s rapidly evolving workplace, and how can leaders prepare for the challenges ahead? 🎧 Tune in to Episode 54 to hear how Melissa Swift is helping organizations and leaders build the workplaces of the future. Be sure to mark your calendars for DSS MIA on Sept 17, where we will focus on THE FUTURE OF APPLIED AI IN THE ENTERPRISE. Join us to hear from experts on how AI is shaping the future of the enterprise. https://www.datascience.salon/miami/

Presented by Andy Terrel, SVP, Data Analytics & Artificial Intelligence at Royal Caribbean Group Data Engineering is exploding, but everyone is just hooking up pipes and triggers. When the next person comes on after your tour of duty, they have to unwind use cases and business logic that never belongs in the ETL script to begin with. There is a better way and it was invented for the semantic web, but almost nobody knows it. In this talk, we look at how to bolt on semantics to your data ecosystem helping to produce fewer bugs, better documented code, true separation of concerns, and faster development.

This presentation delves into the seamless integration of Knowledge Graphs (KGs) and Large Language Models (LLMs) to unlock their collective potential in revolutionizing natural language understanding. By synergizing the structured knowledge of KGs and the text comprehension capabilities of language models, we unlock a powerful combination that bridges the gap between domain-specific, potentially sensitive data, and the vast general knowledge embedded within LLMs. Furthermore, we explore how language models can enrich KGs through efficient knowledge extraction and refinement techniques. This integration opens up a realm of opportunities across diverse domains, from dynamic question-answering systems to context-aware and intelligent chatbots, paving the way for truly transformative applications. Don’t miss this insightful exploration into the world of unified minds!

This session walks through the construction of a RAG (Retrieval Augmented Generation) Large Language Model (LLM) clinical chatbot system, leveraging John Snow Labs’ healthcare-specific LLM and NLP models within the Databricks platform.

ChatGPT, the artificial intelligence chatbot from OpenAI, has taken the world by storm and has transformed the way we perform everyday tasks. With its advanced language processing capabilities, it has become a go-to solution for people looking for quick answers, whether it’s about the weather, the news, or how to cook a recipe. New open source plugins have made it possible for developers to easily build their own ChatGPT knowledge base solutions. At the heart of these solutions is a data model that converts unstructured data from text, videos, images and more into vector embeddings. Vector databases are designed to efficiently store and retrieve these high-dimensional embeddings, making them an ideal solution for chat applications that require fast and accurate vector search results. Join Frank Liu, ML architect at Zilliz, for a session on why vector databases are critical to the success of these LLM-based chat solutions and how developers can build powerful chat solutions that deliver quick answers. Presented by Frank Liu - Director of Operations & ML Architect at Zilliz

Excited to feature Yashasvi Singh, Sr Data Analyst at Navy Federal Credit Union, on the next #DSSBreak! We dove into how strong data governance and analytics can transform business processes and drive strategic decision-making at scale. Yashasvi shared real-world insights on optimizing data stewardship, fostering a culture of trust around data, and aligning analytics initiatives with business goals. If you're passionate about building smarter, more data-driven organizations, this conversation is a must-listen! Thank you, Yashasvi, for sharing your knowledge with our DSS community! #DataGovernance #WomenInData #DSSNYC

Excited for our next DSS Break featuring Anmolika Singh, Data Scientist at Stanley Black & Decker! We’ll explore her journey from studying Applied Data Sciences at Penn State to leading impactful machine learning projects, including real-world applications like sentiment analysis and building interactive Power BI dashboards. Anmolika will also share great advice for aspiring data scientists on balancing technical expertise with leadership and communication skills to drive real business value. If you're passionate about #datascience, #machinelearning, and career growth in tech, this conversation is a must-watch.