Job summary
Job post source
This job is directly from Liberty Mutual
Job overview
The Data Scientist role at Liberty Mutual's Insights & Solutions group focuses on building best-in-class geographic risk segmentation models to support the US Retail Markets business and drive competitive advantage.
Responsibilities and impact
The role involves conducting analyses, building and updating territory factors, developing geographic risk segmentation models, delivering modeling results to stakeholders, engaging with the Data Science community, and applying MLOps practices to data science software.
Compensation and benefits
The salary range is competitive and based on skills, experience, education, and location, with opportunities for progression; benefits include comprehensive health plans, continuous learning, and support for employee well-being.
Experience and skills
Preferred qualifications include actuarial experience with insurance data, proficiency in SQL and Python, experience with GLMs, knowledge of predictive analytics, and some familiarity with geographic and spatial data science; experience requirements vary by education level.
Career development
Liberty Mutual offers continuous learning opportunities and career growth within the role, supported by a purpose-driven and inclusive environment.
Work environment and culture
The company fosters an inclusive, supportive culture valuing diversity, integrity, and employee feedback, with active Employee Resource Groups and a focus on well-being.
Company information
Liberty Mutual is a purpose-driven insurance company committed to innovation, inclusion, and providing protection with care, supporting employees to build meaningful careers.
Team overview
The candidate will join the US Retail Markets Data Science team, the largest group of data scientists at Liberty Mutual, working collaboratively across functional groups to deliver impactful data-driven solutions.
Job location and travel
The role may have in-office requirements depending on candidate location, with offices in multiple cities including California and Philadelphia.
Unique job features
The position offers unique opportunities to work with cutting-edge data science techniques, geographic risk modeling, and MLOps practices in a large, dynamic insurance company.
Company overview
The Muse is a career platform that helps individuals navigate their professional journeys by offering job opportunities, company insights, and career advice tailored to their needs. The company generates revenue through partnerships with employers, providing them with branding solutions and access to a diverse talent pool. Founded in 2011 by Kathryn Minshew, Alexandra Cavoulacos, and Melissa McCreery, The Muse is known for its focus on workplace culture and transparency, offering candidates a unique glimpse into potential employers through multimedia content. It has become a trusted resource for both job seekers and companies aiming to build meaningful connections.
How to land this job
Tailor your resume to emphasize your expertise in predictive analytics, statistical modeling, and experience with geographic and actuarial data, as these are key to the Data Scientist role at The Muse within Liberty Mutual's US Retail Markets Data Science team.
Highlight your proficiency in SQL and Python for data wrangling, visualization, and modeling, and showcase any experience with Generalized Linear Models (GLMs) and MLOps practices to align with the job's technical requirements.
Apply through multiple channels including The Muse's corporate career site, Liberty Mutual's official job portal, and LinkedIn to maximize your chances of being noticed for this position.
Connect with current employees in the Insights & Solutions or US Retail Markets Data Science teams on LinkedIn; start conversations by referencing recent Liberty Mutual data science projects or expressing genuine curiosity about their approach to geographic risk segmentation models.
Optimize your resume for ATS by incorporating keywords such as 'predictive analytics,' 'GLM,' 'SQL,' 'Python,' 'geographic risk segmentation,' and 'MLOps' exactly as they appear in the job description to ensure it passes initial automated screenings.
Use Jennie Johnson's Power Apply feature to automate tailoring your resume, identify all active application portals, and find LinkedIn contacts for networking, allowing you to focus your energy on preparing for interviews and refining your skills.
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