Description

The Actuarial Reserving Support Team within Global Risk Solutions (GRS) Actuarial is seeking an Associate Data Solutions Analyst to support critical data and automation initiatives. This role is a refill for an immediate business need, with the expectation that the successful candidate can quickly contribute while also growing into broader responsibilities over time.

We are looking for individuals with strong logical thinking, a problem-solving mindset, and the ability to learn and adapt quickly. While technical experience is valuable, learning agility and structured thinking are more important than specific tools or years of experience.

This role also supports a longer-term vision of building scalable data pipelines and enabling automation and AI-driven solutions across reserving processes.

Responsibilities

• Develop and enhance data workflows using Python, SQL, and related tools to support reserving activities.
• Apply structured, logical thinking to analyze problems and design efficient, scalable solutions.
• Support automation initiatives, including pipeline development and process optimization.
• Collaborate with actuaries and business stakeholders to translate business needs into data solutions.
• Analyze datasets to identify patterns, issues, and opportunities for improvement.
• Communicate insights and technical concepts clearly to both technical and non-technical stakeholders.
• Contribute to projects involving automation, internal data platforms, and emerging AI capabilities.
• Continuously learn new tools and technologies, applying them to improve existing workflows.

Qualifications

• Strong written and oral communication skills required.
• Bachelors Degree in Computer Science, Computer Engineering, or related discipline preferred
• Master`s in same or related disciplines strongly preferred.
• 1-2 years experience in coding for data management, data warehousing, or other data environments, including, but not limited to, working in NoSQL implementation, ETL, Java, scripting languages (Python, Perl, Shell), and the Hadoop stack.

About Us

Pay Philosophy: 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.

At Liberty Mutual, our goal is to create a workplace where everyone feels valued, supported, and can thrive. We build an environment that welcomes a wide range of perspectives and experiences, with inclusion embedded in every aspect of our culture and reflected in everyday interactions. This comes to life through comprehensive benefits, workplace flexibility, professional development opportunities, and a host of opportunities provided through our Employee Resource Groups. Each employee plays a role in creating our inclusive culture, which supports every individual to do their best work. Together, we cultivate a community where everyone can make a meaningful impact for our business, our customers, and the communities we serve.

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.

Fair Chance Notices

• California
• Los Angeles Incorporated
• Los Angeles Unincorporated
• Philadelphia
• San Francisco