Analyst II, Data Science, Solaria Labs

Solaria Labs is a cross-functional team that partners with teams from across Liberty Mutual to stay on the forefront of disruption, incubating new products, services and experiences to better serve our customers, partners and communities today and in the future.

The Solaria Labs Applied Science team harnesses cutting-edge data science and machine learning to drive the lab’s products and strategic priorities. Our mission is to develop customer-centric solutions and enhance our reputation as industry thought leaders.

We champion a culture of creativity, continuous improvement, and delivery of data science solutions that set new standards of excellence. Join us to be part of a fearless, visionary team and shape the future of the insurance industry.

Discover more at http://www.solarialabs.com 

Job responsibilities

• Collaborate with cross-functional teams across the enterprise to develop innovative predictive and generative AI solutions and solve Liberty’s most challenging data science problems.
• Apply knowledge of sophisticated analytics techniques to manipulate large structured and unstructured datasets in order to generate insights to inform business decisions.
• Identify and tests hypotheses as part of building and developing predictive and generative models for business applications.
• Translate quantitative analyses and results into accessible visuals and high-level presentations for non-technical audiences to help stakeholders interpret the data.
• Enable the business to make trade-offs among choices, with a reasonable view into likely outcomes.
• Customize machine learning solutions to specific client needs.
• Develop solutions to loosely defined problems with guidance from teammates as you iterate on approaches.
• Regularly engage with the data science community and participate in cross-functional working groups.
• Ability to work eastern time is required 

• 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.

Preferred Qualifications

• Breadth of knowledge with feature engineering, traditional machine learning, deep learning, and generative AI.
• Familiarity with common machine learning frameworks (e.g. scikit-learn, PyTorch, Hugging Face, etc.).
• Highly skilled in at least one data science discipline (e.g. computer vision, NLP, etc.).
• Curiosity, ability to learn quickly, and a problem solving mindset.
• Demonstrated ability to collaborate with cross-functional teams, interact with business stakeholders to understand the business problem, and explain complex concepts clearly and concisely.
• Knowledge or experience with integrating multiple modalities (e.g., vision, language, audio) for advanced AI solutions.
• Understanding of DevOps principles and MLOps practices to ensure smooth model deployment, monitoring, and continuous improvement.
• Experience contributing to open-source data science and machine learning projects.