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Data Scientist

Chubb

Salary not specified
Jul 4, 2025
New York, NY, USA
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Chubb is looking for a data modeling expert to leverage statistical and data mining techniques to identify profitable growth areas and optimize portfolio performance, impacting underwriting and marketing functions.

Requirements

  • modeling methodologies
  • dataset generation and transformation
  • statistical programming
  • analysis
  • statistical and data mining techniques
  • extracting and manipulating data using data management tools
  • develop solutions to implement models into production

Responsibilities

  • Build predictive models and analytic solutions, with minimal supervision, to support the underwriting and marketing functions within Chubb.
  • Assist in brainstorming potential data sources that may contain predictive variables.
  • Identify, acquire, evaluate, and document data from these various sources, both internal and external.
  • Collaborate in extracting and manipulating data using data management tools from internal and external data sources.
  • Understand and combine data from various sources to create analytics data sets.
  • Analyze data, draw meaningful conclusions, and assist in developing solutions to help drive profitability and/or growth.
  • Introduce novel methodologies, algorithms, tools, and technologies to solve assigned problems.

Other

  • The position can be based in Jersey City, NJ.
  • Communicate and present findings to business partners to ensure successful integration of projects into business process.
  • Proactively follow up on any issues that were raised during presentations.
  • Work with I/T in the design and testing of models.
  • May lead a small team of direct reports (1-2 analysts).
  • Create goals, oversee projects on a regular basis and provide timely feedback.
  • Provide training guidance and assistance to colleagues.
  • Collaborate with other analytics teams (i.e., Applied AI, Emerging Risks) to achieve objectives.
  • Build partnerships with key counterparts.
  • Monitor the performance and usage of models.
  • Ensure that the reports suit the needs of the audience.
  • Create and maintain clear and concise documentation associated with models.