Job Overview:
Chubb is seeking a highly skilled and experienced Operational Research Data Scientist to join our team. This critical role will be responsible for leading the optimization efforts for a new initiative, leveraging advanced OR techniques and AI technologies to solve core insurance problems dynamically. The ideal candidate will have a proven track record of delivering impactful optimization solutions and be an expert in the application of mathematical models to solve complex business problems.
Job Responsibilities:
- Develop and implement optimization models to improve business performance and operational efficiencies in the insurance industry.
- Analyze large volumes of data and provide insights to make data-driven decisions for use in insurance risk profiling, claims management, and other key problem areas.
- Collaborate with cross-functional teams including actuaries, underwriters, and IT to design, develop, and integrate optimization solutions.
- Lead the end-to-end data science lifecycle from problem definition to model implementation.
- Use AI algorithms and predictive modeling to create dynamic optimization models that can quickly adapt to changing market conditions and customer needs.
- Mentor and train junior data scientists to develop analytical skills in the team.
- Stay up-to-date with the latest OR and AI techniques and explore innovative solutions to stay ahead of the competition.
Qualifications:
- 10+ years of experience in the OR field with a strong understanding of the mathematical underpinning of optimization algorithms.
- Advanced degree (Master's or Ph.D.) in Industrial Engineering, Operations Research, Applied Mathematics, or related fields.
- Expertise in mathematical modeling, optimization, and simulation techniques.
- Experience in deploying OR solutions in the cloud environment.
- Experience with AI algorithms, predictive modeling, and machine learning techniques and their application to insurance problem solving.
- Proficiency in programming languages such as Python, R, and SQL.
- Strong understanding of descriptive statistics and exploratory data analysis techniques.
- Excellent problem-solving and analytical skills with the ability to work with complex datasets.
- Strong communication and collaboration skills to work effectively with different stakeholders and cross-functional teams.
- Experience in leading end-to-end data science lifecycle from problem definition to model implementation.
- Track record of successfully delivering impactful optimization projects in the insurance/finance/retail industries.
- Ability to mentor and train junior data scientists to develop analytical skills in the team.
- Self-driven with a passion for staying up-to-date with the latest OR and AI techniques and exploring innovative solutions to stay ahead of the competition.
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