DataFramed #91 Building a Holistic Data Science Function at New York Life Insurance
Jun 13, 2022
Glenn Hofmann, Chief Analytics Officer at New York Life Insurance, shares his extensive experience in building a robust data science function. He discusses the intricacies of team dynamics and how to offer diverse career paths for data scientists. Glenn dives into the crucial role of MLOps in insurance, enhancing model management and compliance. He also emphasizes the importance of fostering a strong data culture through effective communication and strategic stakeholder engagement, all while navigating the unique challenges of the life insurance industry.
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Glenn's Career Path
- Glenn Hofmann has built three data science functions throughout his career, with his current one being at New York Life Insurance.
- His experience includes roles as a statistics professor and various industry positions, from hands-on modeling to leadership.
Data Science in Life Insurance
- Life insurance offers a diverse range of data science applications, from agent recruiting and productivity prediction to underwriting and fraud modeling.
- These applications leverage various data types and algorithms, including behavioral data, medical data, and neural networks.
Building Data Science Functions
- Building a successful data science function requires talent acquisition, platform and technology investment, and strong relationship building.
- Recruit diverse skill sets, create robust deployment platforms, and maintain consistent communication with stakeholders.