AI Loves Data Podcast

Joyjit Roy shares his experience leading large-scale initiatives across insurance and eCommerce, including multi-year modernization programs that integrate AI into core enterprise systems.

We explore what it takes to move from legacy platforms to intelligent, scalable systems that can support real-time decisioning, MLOps, and next-generation automation.

Key Highlights:

Enterprise AI Modernization: How to integrate AI/ML into legacy systems while maintaining execution speed, governance, and business alignment.

Cloud-Native Transformation: Lessons from building scalable, event-driven architectures that improve agility, observability, and resilience.

MLOps in Practice: Insights into feature engineering, inference workflows, and operationalizing AI for real-world enterprise use cases.

Agentic AI in the Enterprise: Joyjit’s perspective on how agentic systems can enable adaptive decisioning, contextual workflows, and more intelligent automation at scale.

Leading at Scale: Strategies for aligning large, cross-functional teams across product, architecture, engineering, and business stakeholders.

🎧 Tune in to Episode 65 to hear Joyjit Roy’s insights on bridging strategy, delivery, and AI innovation to drive measurable enterprise impact.

Be sure to mark your calendars for the annual ALD NYC on May 13, where we will focus on THE FUTURE OF APPLIED AI IN Finance and Banking. Join us to hear from experts on how AI is shaping the future of finance, banking and insurance: https://ailovesdata.com/newyork/

Use code ALDPODCASTNYC to get 25% off your registration

Writer and Host: Anna Anisin
Produced, edited, and mixed by the Formulatedby Team

Key Highlights:

Production-Scale LLMs: Deploying and scaling recommender systems powered by large language models.

AI Infrastructure Challenges: Building reliable, high-performance search and ML platforms at global scale.

MLOps & Model Optimization: Lessons learned from optimizing and monitoring complex AI pipelines.

Future of AI at Scale: Trends in GenAI, multimodal AI, and recommender systems that will shape the industry.

🎧 Tune in to Episode 63 to hear Rahul Raja’s insights on creating scalable, reliable, and cutting-edge AI infrastructure for production-grade systems.

Be sure to mark your calendars for the annual ALD NYC on May 13, where we will focus on THE FUTURE OF APPLIED AI IN Finance and Banking. Join us to hear from experts on how AI is shaping the future of finance, banking and insurance: https://ailovesdata.com/newyork/ 

Writer and Host: Anna Anisin
Produced, edited, and mixed by the Formulatedby Team

Vaishali shares her experience leading global data teams, partnering with executive leadership, and building strategies that connect cutting-edge technology to real business value. We explore her insights on operationalizing AI, scaling analytics across enterprises, and overcoming challenges in data governance, stakeholder alignment, and innovation adoption.
Key Highlights:
Bridging Tech and Business: How Vaishali connects AI and analytics innovations to organizational strategy and measurable outcomes.
Global Team Leadership: Lessons from managing cross-functional, geographically distributed teams and driving collaboration.
Operational Optimization: Examples of initiatives that reduced operational complexity while improving efficiency.
Scaling Analytics and AI: Best practices for governance, workflow, and embedding AI into enterprise decision-making.
Emerging Trends: Vaishali’s perspective on the next wave of AI, analytics, and enterprise data strategies.
Tune in to Episode 61 to learn how Vaishali Lambe drives data-driven transformation, operational excellence, and AI innovation across global enterprises.
Be sure to mark your calendars for the 10th annual ALD NYC on May 13, where we will focus on GENAI AND INTELLIGENT AGENTS IN THE FINANCE AND BANKING. Join us to hear from experts on how AI is shaping the future of the enterprise. https://www.datascience.salon/new-york/

Writer and Host: Anna Anisin
Produced, edited, and mixed by the Formulatedby Team

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/
As Data Science Salon celebrates 10 years the community unveils a new brand: AI Loves Data

Writer and Host: Anna Anisin
Produced, edited, and mixed by the Formulatedby Team

In this episode of the Data Science Salon Podcast, we sit down with Carlos Aguilar, Head of Product at Hex and former founder of Hashboard, to discuss a topic critical for every data team: how to properly evaluate AI analytics tools.
Carlos shares why traditional checklist-based evaluations fail for conversational AI and generative analytics tools, and how focusing on context, workflow, and real user testing can dramatically improve the chances of success. Drawing on his experience leading the Data Insights team at Flatiron Health, he provides practical guidance for both end-users and data teams.
Key Highlights:
End-User vs Data Team Evaluation: Why both perspectives are crucial for measuring AI effectiveness.
Context Management: How setting up reference questions ensures accurate and relevant answers.
Workflow & Observability: Why monitoring and iterating on AI outputs is essential for real-world success.
Lessons from the Field: Examples of tools that look good in demos but fail in production—and how to avoid those pitfalls.
🎧 Tune in to Episode 60 to learn how to evaluate AI analytics tools the right way and ensure your data teams deploy solutions that actually work in practice.
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/

Writer and Host: Anna Anisin
Produced, edited, and mixed by the Formulatedby Team