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.
