Senior Manager, Decision Science

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.

Data Analytics

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

$120,400.00 - $198,700.00

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At Travelers, our vision is to advance our ability to fuel analytic-driven business decisions by accelerating cross-enterprise collaboration and capabilities. As a Sr. Manager, Decision Science, you will combine data expertise, statistical principles, business understanding, relationship building, and communication skills that will help to advance analytical maturity and business outcomes. Through explanatory modeling and analytics as well as experimental design and related inferential techniques, you will surface actionable insights that influence business decisions and strategies. Simply put, you are helping the business understand 'the why' underneath business trends and data. This discipline focuses on supporting business areas and activities beyond pricing and reserving, including Product, Sales, Marketing, Operations, Human Resources, among others.

This is an individual contributor position.

What Will You Do?

• Utilize a deep understanding of the business to procure data for current and future analysis or prototypes for new data asset, while following coding best practices.
• Seek opportunities to provide stronger data quality and recommend improvements.
• Determine and use appropriate techniques that may include complex diagnostic analysis, active monitoring and/or multivariate methods designed to answer business questions, test hypotheses, or assess impacts and results.
• Explore and propose new data and analytic tools, techniques and industry best practices to apply to business problems.
• Apply appropriate visualization (charts, graphs, maps, etc.) to analytic insights so that they may be delivered to various audiences.
• Interpret and communicate findings to key stakeholders. Recommend optimal business action based on balancing business constraints and analytical findings.
• Leverage existing organizational partnerships across lines and functional teams to influence analytic outcomes and start to inform strategic decisions.
• Be a mentor or resource for less experienced analytic talent, onboard new employees and interns, and provide support for recruiting and talent assessment efforts."
• Perform other duties as assigned.

What Will Our Ideal Candidate Have?

• Experience in Business Insurance nice to have.
• Bachelor’s Degree in a STEM related field, or a Business School Master’s Degree with a concentration in a technical or analytical field.
• Five years of related data and analytic experience.
• Experience using explanatory, diagnostic, and inferential techniques such as experimental design, hypothesis testing, clustering analysis, time series and other statistical modeling algorithms with the ability to decide the appropriate methodology for the purpose.
• Experience working on large-scale multidimensional data using advanced knowledge of open-source cloud-enabled analytical programming languages.
• Ability to foresee challenges and proactively look for ways to create more efficient processes for the business.
• Experience leading and managing complex projects.
• Excellent communication skills with the ability to interact and translate analyses and methodology at various levels of the organization.
• Proactively build and own professional business relationships across the data & analytics community across the Enterprise.
• Core Technical Python (required), R (preferred), SQL, AWS Bedrock / SageMaker, FAISS or equivalent vector databases, NLP/LLM tooling Statistical Methods Experimental design, hypothesis testing, causal inference, time series, clustering, GLMs, predictive modeling

What is a Must Have?

• Bachelor’s degree or four years of experience in data, analytics, engineering, science, technical analytical fields or relevant experience.