Lead AI Product Owner

Chubb; London; On-site; GBP 70,000 - 110,000; Full time

Job summary

An established industry player is seeking a dynamic Applied AI Product Owner to spearhead the design and deployment of cutting-edge analytics capabilities across global insurance products. This role is pivotal in transforming digital underwriting processes through innovative AI solutions. As a leader, you will mentor a diverse team, collaborate with senior executives, and ensure the delivery of high-quality analytics projects. If you are passionate about leveraging data to drive strategic business decisions and have a strong background in machine learning and team management, this opportunity is perfect for you.

Qualifications

• Over 5 years of experience in advanced analytics within insurance or finance.
• More than 2 years of managing technical teams.

Responsibilities

• Lead a diverse team of data science professionals.
• Develop analytical solutions for digital underwriting processes.
• Collaborate with senior executives to deliver scalable AI assets.

Skills

Machine Learning Algorithms

Python Programming

Data Analytics

Team Management

Strategic Thinking

Education

Master's or PhD in a quantitative discipline

Job description

VP, Applied AI

One of Chubb’s most advanced AI analytics products is looking for an Applied AI Product Owner to help build, design, and deploy the capability to multiple insurance products across the globe. This role will work closely with business stakeholders and analytics leadership to change the future of digital underwriting. We are looking for a highly motivated, experienced insurance data science professional to help shape the future of analytics at our company.

Job Description

1. Lead and mentor a diverse team of data science professionals, fostering an inclusive and high-performance culture.
2. Develop analytical solutions to enhance efficiency across the digital underwriting processes for various business units and insurance products.
3. Collaborate with senior executives to define, manage, and deliver scalable AI assets.
4. Facilitate model evaluations with senior stakeholders, effectively communicating complex models to business leadership.
5. Oversee the delivery of cross-functional teams, including data scientists, data engineers, machine learning engineers, and software engineers.
6. Establish integration roadmaps and identify dependencies across different IT deployment systems.
7. Keep abreast of industry-specific trends and developments in data and analytics, exploring new ideas through various internal and external forums.
8. Serve as a subject matter expert, providing guidance to the project team throughout the entire project lifecycle, which includes:

• Identifying and communicating key trends, data limitations, and relevant business stakeholders to the project team.
• Clearly defining the business problem to enable the project team to choose the most appropriate model, analysis, or solution.
• Evaluating the validity of data and/or models prior to presenting them to key business stakeholders.
• Represent the analytics team in training sessions or team meetings organized by the business.
• Collaborate with other Product Owners and Portfolio Managers to identify and address related projects and dependencies.
• Create presentations for business stakeholders to demonstrate product capabilities and provide updates on project status.

Qualifications

• Master's or PhD in a quantitative discipline.
• Over 5 years of professional experience in advanced analytics within an insurance (preferably property and casualty) or financial organization.
• More than 2 years of experience managing technical teams.
• Expertise in machine learning algorithms such as anomaly detection, time series analysis, text analysis and explainability, along with proficiency in Python programming.
• Recognized thought leader on leveraging data and analytics to meet current and future business needs.
• Strategic thinker with the ability to execute tactically and take initiative, while maintaining a strong attention to detail.