
Vijay Yadav
Director of Quantitative Sciences & Head of Data Science at Merck's Center for Mathematical Sciences, with expertise in developing scalable data strategies for pharmaceutical manufacturing.
Top 3 podcasts with Vijay Yadav
Ranked by the Snipd community

8 snips
Mar 21, 2022 • 49min
#81 The Gradual Process of Building a Data Strategy
Vijay Yadav, Director of Quantitative Sciences and Head of Data Science at Merck, brings his expertise in creating scalable data strategies to the discussion. He outlines the 6 critical elements of an effective data strategy, emphasizing the need for a mindset shift within the C-Suite. Vijay shares insights on structuring operational models and fostering a data-driven culture through effective training and enablement. He also highlights the importance of showcasing small wins to build momentum and community around data science.

Mar 30, 2023 • 45min
[Radar Recap] Unleashing the Power of Data Teams in 2023
Join Vijay Yadav, Director of Quantitative Sciences at Merck with over 20 years of data expertise, and Vanessa Gonzalez, Sr. Director of Data Science at Businessolver, as they delve into the art of building high-impact data teams. They share key insights on the need for diverse skill sets and backgrounds, strategic hiring practices, and the critical importance of upskilling within teams. The duo emphasizes balancing technical skills with soft skills to create a thriving culture, ensuring teams can turn raw data into invaluable insights that drive digital transformation.

Oct 16, 2024 • 1h 4min
Vijay Yadav - GenAI-Ready Data
Vijay Yadav, Director of Data Science at Merck, shares insights on integrating generative AI within the pharmaceutical sector. He discusses the critical need for high-quality data and structured approaches to optimize knowledge management and enhance medicine delivery. Vijay emphasizes the importance of linking product structures with transactions and utilizing graph databases for data quality. He also addresses the challenges of unstructured data and the need for user engagement in developing effective AI solutions. The conversation wraps up with thoughts on measuring success and reframing perceptions of AI.