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.
DescriptionThe creative problem solvers in Liberty Mutual’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, you’ll collaborate with teams across Liberty Mutual to deliver analysis that unlocks insights and sparks new, better ways of working.
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 data—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 team’s success now and into the future.
The US Retail Markets Data Science team is looking for an Assistant Director, Data Science in our Property and Specialty Product Design and Modelling team. This is an exciting opportunity to evolve our current process of pricing and underwriting programs deployment pipelines. This highly visible role will collaborate with several disciplines across US Data Science organization to drive this transformation. This individual also have the opportunity to work on other key initiatives and projects in designing the next generation of property and specialty products. A successful candidate should have solid knowledge of the property pricing program development and strong attention to details, and a drive to create an engaging team culture.
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**This is a ranged posting. Level of position offered will be based on skills and experience at manager discretion.**
**This role may have in-office requirements based on candidate location.**
Responsibilities:
• Designs pricing and underwriting programs deployment pipeline from modelling to product launch in coordination with the Deployments team
• Identifies areas for potential process improvements and implements necessary changes to bring products speed to market accurately and efficiently
• Collaborates with Risk Analytics, Delivery, and other teams to successfully implement new pricing programs
• Evaluates and verifies the outputs and processes, promptly communicating any issues that may arise
• Develop line-of-business expertise for the property and specialty pricing and underwriting programs
• Applies knowledge of sophisticated analytical techniques to manipulate structured and unstructured datasets for generating insights to inform business decisions
• Translates quantitative analyses and findings into accessible visuals for non-technical audiences, providing a clear view into interpreting the data
• Enables the business on potential outcomes and provide informative trade-offs among options
• Supports other property and specialty research projects that drives risk segmentation as necessary
• Regularly engages with the data science community and participates in cross-functional working groups
The ideal candidate will have:
• Bachelors with 4+ years, Masters with 2-3 years, or PhD with 0-1 years of relevant experience
• Advanced degree in quantitative field or actuarial credentials highly preferred
• Experience with predictive modeling and statistical software packages (e.g., Excel, Emblem, Python, Earnix) highly preferred
• Strong understanding of rating algorithm structures, including their components, inputs, and outputs, is highly preferred
• Sound knowledge of predictive analytic techniques and statistical diagnostics of models
• Has a value-driven perspective with regard to understanding of work context and impact
• Demonstrated ability to exchange ideas and convey complex information clearly and concisely, both verbally and in writing
• Ability to establish and build effective relationships within and outside the organization
**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 Work® 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.
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