Assistant Director, Data Science

Liberty Mutual is seeking an experienced Gen AI data scientist to join the Service Data Science team within USRM’s Insights & Solutions organization.

The Service organization manages USRM’s customer and agent insurance inquiries, FNOL, and back-office policy processing.

As an Assistant Director, Data Science, that supports the Service organization, this role will help lead Gen AI projects and partner with business as well as technology partners on implementation. We are seeking a self-motivated talent with solid knowledge and hands-on experience in NLP and the generative AI domain, such as prompting LLMs, RAG, speech-to-text models etc. Examples of projects include using service call transcripts to identify customer pain points and analyze customer sentiment; building chat bot across customer service needs; creating real-time service guidance; and implementing auto text fill from speech etc.

**This role may have in-office requirements based on candidate location**

**Level of position offered will be based on skills and experience at manager discretion**

Responsibilities:

• Co-lead complex Gen AI projects from design to production implementation.
• Build POCs (proof of concept) and visualizations to socialize ideas.
• Mine large datasets to generate insights to inform business decisions.
• Communicate effectively with stakeholders to understand requirements, provide updates, and articulate value.
• Collaborate closely with technology and operations teams to ensure seamless deployment and integration of Gen AI models into production.
• Prioritize opportunities based on business impact and create strategic alignment with stakeholders.

The ideal candidate will have:

• Hands on experience with prompting LLMs (such as GPT / Gemini, etc.) for non-trivial tasks (multi-turn conversation, dynamic prompting, etc.)
• Hands on experience with LLM tools such for orchestration (e.g. Langchain, etc.), vectordb stores (e.g. ChromaDB, Postgres, etc.)
• Familiarity with RAG and experience implementing and evaluating RAG pipelines.
• Experience working with Speech to text (STT) models, transcriptions - real time and batch. 
• Proficiency in Python

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.

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.

• Broad knowledge of predictive analytic techniques and statistical diagnostics of models.
• Expert knowledge of predictive toolset; reflects as expert resource for tool development.
• Demonstrated ability to exchange ideas and convey complex information clearly and concisely.
• Networks with key contacts outside own area of expertise. Ability to establish and build relationships within the aligned functional area or SBU.
• Ability to give effective training and presentations to peers, management and less senior business leaders.
• Ability to use results of analysis to persuade team or department management to a particular course of action.
• Has a value driven perspective with regard to understanding of work context and impact.
• Competencies typically acquired through a Ph.D. degree (in Statistics, Mathematics, Economics, Actuarial Science or other scientific field of study) and a minimum of 2 years of relevant experience, a Master`s degree (scientific field of study) and a minimum of 4 years of relevant experience or may be acquired through a Bachelor`s degree(scientific field of study) and a minimum of 5+ years of relevant experience.