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Liberty Mutual Insurance

Data Scientist

Liberty Mutual Insurance, Seattle, Washington, us, 98127

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The 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

Insights & Solutions

team provides critical analysis through five functional groups within

US Retail Markets : Distribution, Marketing & Experience Insights & Solutions Data Office Claims & Service, Insights & Solutions Knowledge & Development Solutions Data Science 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. This role may have in-office requirements depending on candidate location Kickstart your data science career by working on real insurance challenges like pricing, fraud, customer experience, marketing, and claims. If you’re eager to learn, experiment, and make a real impact with data, this program is for you. Who We Are

The US Data Science team at Liberty Mutual is a collaborative group using data and analytics to tackle challenges across personal auto, property, small commercial, claims & service, distribution & marketing, demand & decision science, and data science infrastructure. Our work helps drive smarter decisions, faster and more efficient processes, and better outcomes for both our customers and internal teams. You’ll be part of our Data Science Excellence group: a center of excellence for modeling best practices, data science consulting, and advanced R&D. This team leads the way in developing complex component models and features, including telematics, aerial imaging, insurance scores, and geospatial models. While you’ll be supported by this community, your project work will connect you with teams across the business, giving you exposure to a wide range of data science applications and impact. What you’ll do

Participate in a six-month, hands-on program designed to accelerate your data science career with Liberty’s cloud-native platforms and MLOps best practices. Build your understanding of business and insurance fundamentals through structured training, then join a project team aligned to your interests to tackle business challenges. Develop your skills by working with large datasets, building and validating predictive models, and turning prototypes into production-ready solutions. Translate quantitative findings into clear, actionable recommendations for technical and non-technical stakeholders. Grow your network and skills by teaming up with mentors and peers, joining community groups, and participating in lunch-and-learns, hackathons, and data science events. Transition into a permanent role on a US Data Science team that matches your interests and skills at the end of the program. What you bring

You have a natural curiosity about how organizations use data and analytics to solve real problems and are comfortable operating in a business environment. You’re skilled at breaking down complex ideas and communicating data-driven insights clearly to both technical and non-technical audiences. You have some hands-on experience with enterprise data science platforms (e.g. Snowflake, Databricks, Sagemaker) through coursework or projects and are eager to learn new technologies. You have a solid grasp of basic database concepts (e.g., tables, joins, simple queries). Familiar with exploratory data analysis and data wrangling techniques (e.g. handling missing values, simple transformations) to identify patterns and perform initial data cleaning. You’re interested in code-first data science and reproducible results with Python from data gathering through model scoring using libraries like pandas and scikit-learn; familiar with version control (GitHub) and cloud platforms (AWS). You have strong foundational knowledge of statistics and simple machine learning algorithms (e.g. linear/logistic regression, decision trees) to analyze data, build models, and interpret results with standard metrics (e.g. accuracy, precision, recall). You care about why the work matters with a demonstrated focus on real-world impact and outcomes, not just technical model performance. Bachelor’s or Master’s degree (technical field of study) with relevant project or internship experience, and a demonstrated passion for data science. Qualifications

Data extraction and manipulation skills, EDA, transformations, and general linear models (GLM); preferred skills of basic CART and GLM. Foundational knowledge of predictive analytics tools. 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 a Master`s degree (in Statistics, Mathematics, Economics, Actuarial Science or other scientific field of study) and no professional experience or may be acquired through a Bachelor`s degree and 3+ years of relevant experience. 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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