AVP, Lead Data Scientist

AVP, Lead Data Scientist

Chubb’s North America Property and Casualty Data Analytics Division is currently seeking an experienced Lead Data Scientist with 7+ years of industry experience to join our fast-paced, high-energy team.

As a Lead Data Scientist for NA PC Analytics, you will perform quantitative data analysis to enable organizational decision making and develop solutions to complex business problems and create value to the business.

This position offers exposure to a wide variety of analytics tools and technologies as well as unique challenges in problem-solving.

In this role, you will :

• Provide leadership and oversight to project teams creating advanced statistical models, including commercial insurance pricing models
• Synthesize data to uncover inherent trends, assess impact of data on business usage, and to make recommendations for improvement
• Research, recommend, and implement statistical and other mathematical methodologies appropriate for the given business problem
• Builds and deploys generalized linear models in support of our pricing modeling efforts for business lines such as homeowners, property, and casualty
• Performs data validation and exploratory data analyses
• Communicates analytical goals, approach, outcomes, and insights to both technical and non-technical audiences
• Translate analytical findings into relevant business insights
• 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
• Effectively communicate with key stakeholders (both technical and non-technical) in written, oral and presentation formats
• Create / Maintain excellent working relationships with business partners across the Chubb organization including Field, Product, Operations, IT and analytics peer groups.
• Lead teams of junior data scientists and engineers and provide guidance and mentorship directly and indirectly

Required :

• Superb programming experience in Python
• Excellent ML modeling skills
• Advanced understanding of predictive and prescriptive analytics and data visualization.
• Strong leadership skills to provide guidance and direction to project teams.
• Data manipulation and feature engineering
• Exploratory data analysis and model development and solution design
• Excellent programming experience in SQL
• Ability to communicate effectively to both technical and non-technical audiences in written, oral and presentation format
• The ability to multi-task, learn new things quickly, and demonstrate excellent problem-solving skills.
• GLM (Generalized Linear Modeling) in support of building pricing models for products such as homeowners, and property and casualty
• Working knowledge / familiarity with Git version control

Preferred :

• Experience in architecting and consuming APIs at scale
• Hands-on experience with big data technologies and cloud (Databricks / Spark, Azure / AWS / GCP)
• A / B testing experience for quality engineering

Nice to have :

• Prior insurance and / or financial services sales / marketing experience
• Advanced knowledge of model tuning, evaluation, and operationalization
• Prior exposure to NoSQL databases

Education :

The candidate should have 7+ years of industry experience in data science and analytics. Graduate degrees in a technical field such as Statistics, Computer Science, Data Science, Bioinformatics, Physics, Mathematics, Economics or Engineering are preferred

Location :

• We are open to the following work locations for this position : (Philadelphia, PA - Jersey City, NJ - Whitehouse Station, NJ - Simsbury, CT)
• Please note, there will be limited expected travel to various work locations for in person collaboration and meetings

The pay range for the role is $122,500 to $198,000. The specific offer will depend on an applicant’s skills and other factors.

This role may also be eligible to participate in a discretionary annual incentive program. Chubb offers a comprehensive benefits package, more details on which can be found .

The disclosed pay range estimate may be adjusted for the applicable geographic differential for the location in which the position is filled.