Chief of Data Science and Analytics for InsuraMatch

Chief of Data Science and Analytics for InsuraMatch

  • Anywhere

Company Name:-
The Travelers Companies, Inc.

Job Location:-
Boston, MA 02101

Job Summary:-
Company Summary
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 160 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.

Target Openings
1
Job Description Summary
InsuraMatch is an independent agency company, owned by Travelers Insurance, that uses an innovative online platform to help consumers compare offerings from more than 40 carriers across the United States.

With a focus on personal insurance, InsuraMatch offers overage for auto, home, boat, motorcycle, renters, umbrella, and flood, among others.

InsuraMatch operates independently and manages all carrier partnerships.

InsuraMatch is looking to hire a versatile Chief of Data Science and Analytics to lead and grow a team in expanding a robust data infrastructure, establishing operational and management reporting, and pioneer work on advanced analytics initiatives such as acquisition targeting, retention modeling, call routing and lifetime value analyses.

In this role you will be a critical factor in driving the profit and customer growth of this growing insurance agency.

InsuraMatch is part of Travelers Insurance and this role will be expected to partner with the Travelers team in order to share best practices and leverage support wherever possible.

This role is a manager.

Primary Job Duties & Responsibilities
Data Science:
Responsible for analyzing large, complex data sources to generate actionable insights and solutions that better serve our customers.

Regularly interact with business partners to identify questions and issues for data analysis and experiments.

Using statistical and machine learning algorithms to build sophisticated models that solve important business problems.

Examples may include building models related to consumer shopping behavior, quote/purchase behavior, sales/service operations, retention/lifetime customer value, contributions to overall margin, and customer satisfaction.

Using appropriate artificial intelligence techniques to analyze text and other unstructured dat

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