Assistant Director/Director I, Data Science

Location
98101, Seattle
Salary
Open
Posted
Nov 18, 2021
Closes
Jan 17, 2022
Ref
95826772#GIJ--LibertyMutual.1
Job Type
Not Specified
Career Level
Not Specified

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 Work® US for the past several years. We were also selected as one of the 100 Best Places to Work in IT onIDG'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 Graduatesas 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. 

Summary: Collaborates with business partners to develop predictive analytic solutions and/or tools that enable data driven strategic decision making. Utilizes current and emerging data science techniques to manipulate large structured and unstructured data sets, identify patterns in raw data, and develop models to predict the likelihood of a future outcome and/or to optimize business solutions. This level reflects broad knowledge of predictive analytics techniques, and general application of applying those techniques to business issues. This position will be primarily focused on price modeling for Business Lines Package products with specific drilldowns into GL and Property perils, and may also provide opportunities to model in other lines of business. Frequent communication with stakeholders and business partners will be necessary to ensure buy-in and alignment on both the framing of business problems and strategy to implement data-driven solutions.

 

Responsibilities Include

  • Applies broad knowledge of sophisticated analytics techniques to manipulate large structured and unstructured data sets in order to generate insights to inform business decisions
  • Identifies new strategic opportunities for use of theoretical and practical methods and tools; applies forward looking thinking to inform methodological advancement; drives innovation in the application and development of tools and practices
  • Mines large data sets using analytical techniques to generate insights and inform business decisions
  • Identifies and tests hypotheses, ensuring statistical and practical significance, and builds predictive models for business application
  • Translates quantitative analyses and findings into accessible visuals for non-technical audiences, providing a clear view into interpreting the data
  • Regularly engages with business partners and stakeholders on business problems and solutions; enables the business to make clear trade-offs between and among choices, with a reasonable view into likely outcomes
  • Responsible for larger components of highly complex projects; guides aspects of project design as a technical consultant for the team
  • Customizes analytic solutions to specific client needs.
  • Regularly engages with the data science community and leads cross functional working groups
  • The actual internal level/grade for this role will depend on the candidate's overall experience and skill level 

  • Broad knowledge of predictive analytic techniques and statistical diagnostics of models; advanced knowledge of predictive toolset; reflects as expert resource for tool development
  • Demonstrated ability to exchange ideas and convey complex information clearly and concisely
  • Ability to establish and build relationships within and outside the organization
  • Familiarity with insurance product sets, pricing and segmentation concepts
  • Ability to give effective training and presentations to management and other groups; ability to use results of analysis to persuade team, department management or senior management to a particular course of action.
  • Broad knowledge of business drivers and market context; has a value driven perspective with regard to understanding of work context and impact.
  • Competencies typically acquired through achievement of ACAS/FCAS or a Ph.D. degree (in Statistics, Mathematics, Economics, Actuarial Science or other scientific field of study) and 3 years of relevant experience, a Master`s degree (scientific field of study) and 6 years of relevant experience or may be acquired through a Bachelor`s degree (scientific field of study) and 8 years of relevant experience.
  • Python expertise strongly preferred 

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