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Senior Analyst, Data Science Underwriting Modeler

Unavailable
Full-time
Remote
United States

Pay Philosophy

The typical starting salary range for this role is determined by a number of factors including skills, experience, education, certifications and location. The full salary range for this role reflects the competitive labor market value for all employees in these positions across the national market and provides an opportunity to progress as employees grow and develop within the role. Some roles at Liberty Mutual have a corresponding compensation plan which may include commission and/or bonus earnings at rates that vary based on multiple factors set forth in the compensation plan for the role.

Description

The creative problem solvers in Liberty Mutualโ€™s Insights & Solutions group harness the power of data, analytics and technology to develop innovative solutions that drive our US Retail Markets business forward and support a high-performing culture. This group brings together highly talented thinkers and doers ready to challenge the status quo and make an impact. As a member of this cross-functional group, youโ€™ll collaborate with teams across Liberty Mutual to deliver analysis that unlocks insights and sparks new, better ways of working.

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The US Retail Markets Data Science team brings together a diverse range of talent to predict future risk and what our customers will need to recover. Our data engineers write code that turns trillions of bits of information into structured dataโ€”data that our hundred-plus Data Scientists analyze with cutting-edge modeling techniques to unlock insights. From there, our tools and deployment teams ensure this data can be practically applied to business problems across US Retail Markets. Join us and be a part of this dynamic group driving industry-leading data segmentation, fueling the teamโ€™s success now and into the future.

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The Auto Product Design and Modeling Department of US Retail Markets is hiring an individual contributor for its Underwriting and Fraud team. The team develops sophisticated models that are used for Underwriting actions. The Individual Contributor role will report to the team Manager and will build predictive models to improve the effectiveness of our underwriting actions and improve profitability for Personal Lines Auto. The ideal candidate is proactive and intellectually curious, highly technical, and can think through complex business questions efficiently.

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**Click HERE to hear to learn more about this exciting opportunity**

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**This is a ranged posting. Level of position offered will be based on skills and experience at manager discretion.**

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**This role may have in-office requirements based on candidate location.**

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ย Responsibilities:

  • Research strategies and methodologies for new applications of advanced modeling techniques to inform underwriting decisions across Personal Lines.
  • Build, refine, evaluate, and deploy GLM and ML models.
  • Understand our UW rules and processes in great detail; determine predictive modeling strategies to improve process and profitability outcomes.
  • Collaborate with Delivery, State, IT, and various Personal Lines experts across the organization to develop and implement models.
  • Present recommendations to key stakeholders.
  • Engage with the Data Science community.

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The ideal candidate will have:

  • Strong analytical skills with solid understanding of predictive modeling concepts and techniques.ย  Experience with statistical software packages (e.g., R, SAS, Python, and Emblem) desired.
  • Strong knowledge of insurance operations and the procedures of Financial, Underwriting, Claims, Statistical, Information Technology, Legal, and Sales departments.
  • High-level knowledge of data sources, tools, and the business (lines, systems, pricing plans).
  • Ability to exchange ideas and convey complex information clearly and concisely, both verbally and in writing.
  • Has a value-driven perspective with regard to understanding of work context and impact.

Qualifications

  • Solid knowledge of predictive analytics techniques and statistical diagnostics of models.
  • Advance knowledge of predictive toolset; expert resource for tool development.
  • Demonstrated ability to exchange ideas and convey complex information clearly and concisely.
  • Has a value-driven perspective with regard to understanding of work context and impact.
  • Competencies typically acquired through 0-1 yrs. of related experience with a Ph.D., a minimum of 2-3 yrs. of experience with a masterโ€™s degree, a minimum of 4+ yrs. of experience with a bachelorโ€™s degree.

About Us

**This position may have in-office requirements depending on candidate location.**

At Liberty Mutual, our purpose is to help people embrace today and confidently pursue tomorrow. That's why we provide an environment focused on openness, inclusion, trust and respect. Here, you'll discover our expansive range of roles, and a workplace where we aim to help turn your passion into a rewarding profession.

Liberty Mutual has proudly been recognized as a "Great Place to Work" by Great Place to Workยฎ US for the past several years. We were also selected as one of the "100 Best Places to Work in IT" on IDG's Insider Pro and Computerworld's 2020 list. For many years running, we have been named by Forbes as one of America's Best Employers for Women and one of America's Best Employers for New Graduates as well as one of America's Best Employers for Diversity. To learn more about our commitment to diversity and inclusion please visit: https://jobs.libertymutualgroup.com/diversity-inclusion

We value your hard work, integrity and commitment to make things better, and we put people first by offering you benefits that support your life and well-being. To learn more about our benefit offerings please visit: https://LMI.co/Benefits

Liberty Mutual is an equal opportunity employer. We will not tolerate discrimination on the basis of race, color, national origin, sex, sexual orientation, gender identity, religion, age, disability, veteran's status, pregnancy, genetic information or on any basis prohibited by federal, state or local law.

Fair Chance Notices