Assistant Director, Data Science, Reserve Modeling

Description

The insurance industry is undergoing tremendous change and Liberty Mutual, a diversified global insurer and third largest property and casualty insurer in the US, is leading the charge with its innovative products and customer-centric approach within both its personal and commercial units. Liberty Mutual's United States Retail Markets is seeking an Assistant Director, Data Science in the Risk Analytics Reserve Modeling team to develop claim-level models supporting both personal and small commercial lines of business.

In this role, you will work to continue advancing our understanding of and ability to predict loss and loss adjustments expenses through new data sources, tools, analytics, and advanced modeling techniques. This person will also work directly with our business stakeholders in supporting the implementation of our work into the business, including understanding the business needs and the best ways to continually improve our models and analytics. This position requires candidates who are intellectually curious, and love to support our business partners.

This position may have in-office requirements dependent upon candidate location.

Responsibilities:

• Collaborate with other business partners to develop appropriate statistical approaches and tools that will drive strategic decision making related to Reserving, trends, and other challenging problems central to our business.
• Identify new strategic opportunities for the use of theoretical methods and tools.
• Apply forward looking thinking to inform methodological advancement.
• Drive innovation in the application and development of tools and practices.
• Mine large data sets using sophisticated analytical techniques to generate insights and inform business decisions.
• Identify and tests hypotheses, ensuring statistical significance, and build predictive models for business applications.
• Translate quantitative analyses and findings into accessible visuals for non-technical audiences, providing a clear view into interpreting the data.
• Enable the business to make clear tradeoffs between and among choices, with a reasonable view into likely outcomes.
• Responsible for larger components of highly complex projects.
• Guide aspects of project design as a technical consultant for the team.
• Customize analytic solutions to specific client needs.
• Regularly engage with the data science community and leads cross functional working groups.

• Strong foundation in Data Science and Machine Learning.
• Expert analytical/problem solving and research skills.
• Proficiency in Python, SAS and/or SQL.
• Hands-on experience with large analysis datasets and Enterprise-scale database systems.
• Ability to perform high-level work both independently and collaboratively as a project team member or leader.
• Strong verbal and written communication skills, and ability to exchange ideas and convey complex information clearly and concisely.
• Ability to use results of analysis to persuade team or department management to a particular course of action.
• Knowledge of insurance principles, underwriting and ratemaking concepts and the various functions of an insurance organization, including Claims, Pricing, Underwriting, and Finance desirable.
• Ability to work ET hours.

• Broad knowledge of predictive analytic techniques and statistical diagnostics of models.
• Expert knowledge of predictive toolset; reflects as expert resource for tool development.
• Demonstrated ability to exchange ideas and convey complex information clearly and concisely.
• Networks with key contacts outside own area of expertise. Ability to establish and build relationships within the aligned functional area or SBU.
• Ability to give effective training and presentations to peers, management and less senior business leaders.
• Ability to use results of analysis to persuade team or department management to a particular course of action.
• Has a value driven perspective with regard to understanding of work context and impact.
• Competencies typically acquired through a Ph.D. degree (in Statistics, Mathematics, Economics, Actuarial Science or other scientific field of study) and a minimum of 2 years of relevant experience, a Masters degree (scientific field of study) and a minimum of 4 years of relevant experience or may be acquired through a Bachelors degree(scientific field of study) and a minimum of 5+ years of relevant experience.

• California
• Los Angeles Incorporated
• Los Angeles Unincorporated
• Philadelphia
• San Francisco