Director, Data Science - Product Design and Modeling, Business Lines

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

Liberty Mutual’s Global Retail Markets (GRM) Product Design and Modeling team is hiring an individual contributor to work on predictive modeling for our Business Lines core programs. The ideal candidate is proactive and intellectually curious, highly-technical, and can efficiently think through complex business questions. They reflect 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 Auto, but will 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. Although this is an Senior Technical Professional (STP) position, there will be some managerial oversight of a sub-team of contractors to develop and deploy several enhancements to our pricing segmentation products and processes.

This exciting and highly-technical role:

• 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
• 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
• Oversees work of team of contractors as well as occasional ADP resources aligned with our projects

• 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
• Managerial experience with an intern or rotator is a plus but not required
• 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.