Senior Data Scientist

Senior Data Scientist

The Data Science team of the North America Data Analytics division at Chubb is seeking an experienced Senior Data Scientist with 4+ years of industry experience to join our fast-paced, high-energy team. This team is responsible for building data pipelines and delivering predictive modeling and data science solutions to our business partners that will meet business objectives and move-the-needle to improve upon key performance metrics.

As a Senior Data Scientist, you will develop and apply generalized linear models / machine learning solutions to complex business problems to create value for the business. This position offers exposure to a wide variety of analytics tools and technologies as well as unique challenges in problem-solving. Be ready to leverage internal/external data sources as you lead, develop, deploy, and monitor best-in-class model solutions.

In this role you will:

• Be responsible for and lead the continued development / delivery of new and existing processes.
• Collaborate with business partners and peers within the organization to understand and scope the problem, gather business requirements, and develop robust model solutions that drive improvement in key business metrics.
• Execute all aspects of analytics initiatives including exploratory data analysis, data preprocessing, model development, model deployment and monitoring.
• Synthesize data, to uncover inherent trends in data, to assess impact of data on business usage, and to make recommendations for improvement.
• Thoughtfully identify and construct predictive variables from both internal and external data sources.
• Research, recommend, and implement statistical and other mathematical methodologies appropriate for the given business problem.
• Create/Maintain excellent working relationships with business partners across the Chubb organization including Product, Actuarial, IT, and analytics peer groups.
• Provide supporting documentation for the models developed including documentation of methodologies used, data issues encountered, and responses to regulatory requests.