Analytics Product Engineer, AI Intake

Who Are We?

Taking care of our customers, our communities and each other. That’s the Travelers Promise. By honoring this commitment, we have maintained our reputation as one of the best property casualty insurers in the industry for over 170 years. Join us to discover a culture that is rooted in innovation and thrives on collaboration. Imagine loving what you do and where you do it.

Technology

Compensation Overview

The annual base salary range provided for this position is a nationwide market range and represents a broad range of salaries for this role across the country. The actual salary for this position will be determined by a number of factors, including the scope, complexity and location of the role; the skills, education, training, credentials and experience of the candidate; and other conditions of employment. As part of our comprehensive compensation and benefits program, employees are also eligible for performance-based cash incentive awards.

Salary Range

$126,500.00 - $208,700.00

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Travelers Data Engineering team constructs pipelines that contextualize and provide easy access to data by the entire enterprise. As an Analytics Product Engineer, you will play a key role in growing and transforming our analytics landscape. In addition to your strong analytical mind, you will bring your inquisitive attitude and ability to translate stories found in data by leveraging a variety of data programming techniques. You will leverage your ability to design, build and deploy data solutions that capture, explore, transform, and utilize data to support Artificial Intelligence, Machine Learning and business intelligence/insights.

What Will You Do?

Product Ownership & Strategy

• Define and prioritize the product backlog and roadmap for our AI Intake Platform, focusing on both expansion of the platform as well as improvements to the data extraction pipeline, leveraging Generative AI Techniques
• Act as the voice of the decision science and Management Liability groups, ensuring their needs drive platform evolution
• Measure performance through KPIs and adjust the roadmap based on real outcomes achieved and the needs of the business
• Make critical trade-off decisions in collaboration with leadership to maximize value delivery

Solution Development & Prototyping

• Prototype and iterate on solutions in real-time using modern platform services, GenAI capabilities, and advanced analytics tools
• Leverage keen data analytics skill set to uncover patterns in the data and identify future enhancements to the data pipeline
• Partner with decision science and IT teams to develop prototypes using GenAI, machine learning algorithms, and statistical techniques to solve extraction challenges and enhance the underwriting workflow
• Partner with users to test and validate solutions in their actual working environment, ensuring real-world effectiveness
• Build proof-of-concepts for new capabilities before IT implementation
• Prototype solutions that demonstrate feasibility and de-risk IT implementation

Tool & Automation Development

• Build and operationalize data solutions that capture, transform, and utilize data to support AI/ML and business intelligence initiatives
• Develop automation for repetitive actuarial processes and workflows
• Build automation that directly impacts pricing outcomes or operational efficiency
• Create templates and reference implementations that accelerate future model deployments

Stakeholder & Delivery Management

• Gather and document requirements from teams across Management Liability and Research and Development
• Scope work and create clear specifications for IT delivery teams
• Manage IT delivery partnerships and monitor delivery to ensure solutions meet business needs
• Manage stakeholder expectations and communicate progress
• Facilitate knowledge transfer between business teams and IT

Platform Evolution & Best Practices

• Identify patterns across multiple team engagements to inform platform-level abstractions and reusable components
• Collaborate with IT and engineering teams to generalize and scale successful prototypes into platform capabilities
• Implement "test and learn" experimentation to continuously refine and improve platform capabilities
• Create clear documentation on which datasets to use for different modeling purposes
• Establish and evangelize best practices for SQL, Python, and cloud usage across teams
• Share insights and best practices across teams to ensure alignment and consistency in analytical approaches

What Will Our Ideal Candidate Have?

• Bachelor’s Degree in STEM related field or equivalent
• Eight years of related experience
• Highly proficient use of tools, techniques, and manipulation including Cloud platforms, programming languages, and a full understanding of modern software engineering practices.
• The ability to deliver work at a steady, predictable pace to achieve commitments, deliver complete solutions but release them in small batches, and identify and negotiate important tradeoffs.
• Demonstrated track record of domain expertise including understanding technical concepts necessary and industry trends, and possess in-depth knowledge of immediate systems worked on and some knowledge of adjacent systems.
• Strong problem solver who ensures systems are built with longevity and creates innovate ways to resolve issues.
• Strong written and verbal communication skills with the ability to work collaborate well with team members and business partners.
• Ability to lead team members and help create a safe environment for others to learn and grow as engineers. and a proven track record of self-motivation in identifying opportunities and tracking team efforts.

What is a Must Have?

• Bachelor’s degree or equivalent training with data tools, techniques, and manipulation.
• Four years of data engineering or equivalent experience.