In this podcast episode, Naomi Yudanin, the Director of Medical Data at Munich Re, discusses the relevance of domain-specific data science expertise. She shares her journey, starting in biochemistry and molecular biology, transitioning into systems immunology, and eventually ending up in medical data and EHR product management. She emphasizes the importance of understanding the objective of generating insights from data and how clear business objectives and proper questions drive successful data analysis in healthcare. Beyond the typical technical questions, Naomi encourages stakeholders to think about the stories they want to tell with their data. She links them to the business value to derive actionable insights. She also touches on the perception of data quality in the healthcare industry and how the interpretation of analytics can result in different business outcomes.

Highlights

01:42 Understanding the Role of Domain-Specific Knowledge in Data Science

03:33 The Value of Domain Expertise in Data Science

04:24 Challenges and Advantages of Having a Non-Technical Background

07:30 The Importance of Understanding the Data and its Relevance

10:14 The Gap between Business Outcomes and Technical Delivery

16:27 The Role of Data in Achieving Business Outcomes

19:29 The Importance of Telling the Right Story with Data

Dr. Naomi Yudanin is currently the Director of Medical Data at Munich Re, a leading global provider of reinsurance, primary insurance and insurance-related risk solutions. Throughout her career, Naomi has integrated healthcare domain expertise with machine learning approaches to derive clinically relevant insights and provide actionable guidance for health product development and care delivery. Prior to joining Munich Re, Dr. Yudanin led enterprise-wide AI/ML development in several health tech startups, most recently as the Chief Data Scientist at Nanowear. Naomi obtained a PhD in Systems Immunology at Columbia University, where she received the Parker Graduate Award for innovative research, and completed a postdoctoral fellowship in computational genomics at Weill Cornell. The results of her research comprise multiple publications in high-impact journals, including Cell, Science, and Nature. Since transitioning to industry, Naomi has been awarded over $2 million in grants and co-authored two patents for AI/ML applications in healthcare. She continues to serve on the NIH study section for translational AI and as an advisor on several SBIR awards and regulatory committees focused on digital health.

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