Interns will apply statistical and machine learning techniques to solve quantitative problems within the insurance industry, focusing on areas like Claims, Lifetime Value Estimation, or Marketing. They will also expand their skills through hands-on training and present their findings to leaders and stakeholders.

The role involves analyzing and modeling large datasets, including web traffic and content signals, to optimize business operations, product development, and growth. Key tasks include developing and deploying scalable machine learning models and building ETL pipelines using GCP and BigQuery.

The Applied Data Scientist will own the data foundation by preparing, cleaning, and transforming raw data into high-quality features for modeling, while also participating in the full modeling lifecycle from analysis to iteration on machine learning models. This role involves investigating data discrepancies, designing automated frameworks for accuracy, and collaborating cross-functionally to define the centralized feature store.

The Senior Data Scientist will leverage advanced analytics, machine learning, and AI to generate actionable insights that drive business decisions and project outcomes and support data and AI use cases. This role focuses on analyzing complex datasets, building predictive models, ...