Data Scientist: Property & Specialty Product Design & Modeling

The creative problem-solvers in Liberty Mutual’s USRM Data Science 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.

Join the Property & Specialty Product Design & Modeling department to develop industry-leading pricing and underwriting models. We pride ourselves in developing the best-in-class models and making the team an awesome place to work! The P&S PDM team turns DS insights into business value and partners closely with business stakeholders to expertly align risk with rate.

Analyst roles within the team range from leaning more heavily into research to inform our product design, to directly interfacing with regulators and Profit & Loss owners. Our analysts make an impact by improving model fits, researching new modeling techniques, increasing the speed of model deployments, improving capabilities to test, calibrate, and monitor models, and serving as technical experts to explain our models to the broader Property & Specialty organization. With opportunities for growth, mentorship, and engagement with the data science community, we offer a stimulating environment for those with a passion for technical excellence and problem-solving.

The Analyst collaborates with business partners to develop predictive analytic solutions that enable data-driven strategic decision-making.  This role utilizes 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 solid knowledge of predictive analytics techniques, while continuing to learn how to apply techniques to business issues.

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

Candidates who live within 50 miles of Boston, MA; Portsmouth, NH; Seattle, WA; Columbus, OH; or Plano, TX will follow a hybrid schedule, coming into the office two days per week. Otherwise, this role is remote.

Responsibilities:

• Assist on design of designing pricing programs deployment pipeline from modelling to product launch in coordination with the Deployments team
• Applies knowledge of sophisticated analytics techniques to manipulate large structured and unstructured data sets in order to generate insights to inform business decisions.
• Identifies and tests hypotheses, ensuring statistical significance, as part of building and developing 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.
• Enables the business to make clear trade-offs between and among choices, with a reasonable view into likely outcomes.
• Customizes analytic solutions to specific stakeholder needs.

• Collaborates with other data science teams to successfully implement new pricing programs using Python packages as desired.

• Responsible for smaller components of projects of moderate-to-high complexity.
• Supports other property and specialty pricing programs including building models and rollouts with adjusting models due to state restrictions, building supporting documents and responding to DOI objections
• Regularly engages with the data science community and participates in cross-functional working groups.

• 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 master’s degree, a minimum of 4+ yrs. of experience with a bachelor’s degree.