Chubb’s North America Data and Analytics Division is currently seeking an experienced Senior Data Scientist with 5+ years of industry experience to join our fast-paced, high-energy team. As a Senior Data Scientist for NA 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. Building and deploying predictive models in support of our pricing strategy will be a focus area.
In this role, you will:

• Synthesize data to uncover inherent trends, assess impact of data on business usage, and to make recommendations for improvement.
• Build GLM pricing models in support of various property and casualty insurance products.
• Research, recommend, and implement statistical and other mathematical methodologies appropriate for the given business problem.
• Build explanatory and forecasting models using descriptive and inferential statistics, and regression analysis.
• Perform data validation, preprocessing, 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 Product, Actuarial, IT, and analytics peer groups.
• Provide guidance and mentorship directly and indirectly to junior team members.

Required:
o Extensive experience with both supervised and unsupervised ML algorithms, including GLMs (Generalized Linear Models).
o Strong understanding of predictive and prescriptive analytics and data visualization.
o Extensive experience with data manipulation and feature engineering.
o Exploratory data analysis, model development and solution design.
o Significant programming experience in Python.
o Significant programming experience in SQL.
o Working knowledge/familiarity with Git version control.
o Ability to communicate effectively to both technical and non-technical audiences in written, oral and presentation formats.
o The ability to multi-task, learn new things quickly, and demonstrate excellent problem-solving skills.

Preferred:
o Prior experience in property and casualty insurance, and / or knowledge of actuarial concepts.
o Advanced knowledge of model tuning, evaluation, and operationalization.
o Experience in architecting and consuming APIs at scale.
o Experience with Deep Learning libraries (Tensorflow / Keras, PyTorch, MXNet, etc.).
o Hands-on experience with big data technologies and cloud (Databricks / Spark, Azure/AWS/GCP/Snowflake).
o Experience with Text Analytics and Natural Language Processing.
o Comfortable with command line (Linux, Windows) scripting.
o Experience with at least one other programming language aside Python, like Julia, R Scala, Go, Java, or C++.

Education:
• The candidate should have 5+ 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 - New York, NY - Simsbury, CT)

The pay range for the role is $114,100 to $193,900. 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 on our careers website. The disclosed pay range estimate may be adjusted for the applicable geographic differential for the location in which the position is filled.