Lead Operations Research Data Scientist

CHUBB
London
9 months ago
Applications closed

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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 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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