Senior Data Scientist, Agentic AI

Guardian Life Insurance•Boston, MA

21h•Hybrid

About The Position

Guardian is undergoing a transformation to become a modern, forward-thinking insurance company focused on enhancing customer wellbeing. This role offers a unique chance to leverage cutting-edge AI for business transformation. The Data & AI team at Guardian fosters a culture of intelligence and automation, creating business value through advanced data and AI solutions. This team comprises data scientists, engineers, analysts, and product leaders dedicated to delivering AI-driven products that drive growth, improve risk management, and elevate customer experience. The Data Science Lab (DSL) was established to reimagine insurance by incorporating emerging technology, evolving consumer needs, and rapid AI advancements. The DSL accelerates Guardian's transition to data-driven decision-making and promotes innovation through rapid testing, scaling, and operationalization of state-of-the-art AI. We are seeking a Senior Data Scientist, Agentic AI, an individual contributor with deep expertise in Agentic AI, large language models (LLMs), and natural language processing (NLP), who has a proven history of delivering enterprise-level AI/ML solutions and products. In this position, you will collaborate with a team led by a Lead Data Scientist to develop and deploy advanced agentic AI and LLM-powered solutions aimed at automating business workflows, enhancing decision-making, and achieving measurable business outcomes. You will work closely with cross-functional teams, including other Data Science, Data Engineering, and Business groups. Successful candidates will possess a strong technical foundation, excel in coding, be detail-oriented, and demonstrate a passion for analytical thinking and problem-solving.

Requirements

PhD with 2+ years, Master’s with 4+ years of experience in Computer Science, Engineering, Statistics, Applied Mathematics, or related field.
3+ years of hands-on experience in AI/ML modeling and development, with a primary focus on agentic AI, LLMs, and NLP.
Deep expertise in LLMs, generative AI, agentic systems, NLP, and multi-step reasoning architectures (e.g., LangGraph, RAG, agent frameworks).
Strong programming skills in Python and familiarity with frameworks such as PyTorch, TensorFlow, Hugging Face Transformers, and LangChain.
Demonstrated experience building, fine-tuning, and deploying LLMs and NLP solutions in production environments.
Working knowledge of classical machine learning techniques (e.g., clustering, regression, XGBoost, Random Forest, decision trees) and their practical applications.
Experience with data wrangling, distributed computing, and applying parallelism to ML solutions.
Proven experience in providing technical leadership and mentoring to data scientists and strong project management skills with ability to monitor/track performance for enterprise success
Working knowledge of core software engineering concepts (version control with Git/GitHub, testing, logging, CI/CD).
Excellent analytical, problem-solving, and communication skills.
Must be legally authorized to work in the United States, without the need for employer sponsorship now or in the future.

Nice To Haves

Background in insurance and underwriting preferred
Experience in insurance, financial services, or related industries is a plus.

Responsibilities

Lead the design and implementation of agentic AI solutions and LLM-powered applications that automate business processes and improve customer and employee experiences.
Drive the end-to-end model lifecycle: data exploration and preparation, model finetuning, validation, deployment, and monitoring, ensuring quality, security, scalability, and fairness.
Apply LLMs and generative AI to process and interpret unstructured data (e.g., insurance applications, underwriter’s notes, medical records, customer interactions).
Develop autonomous agents, multi-step reasoning systems, and advanced NLP pipelines that integrate with Guardian’s platforms.
Translate research in agentic AI, LLMs, and reinforcement learning into practical, production-ready solutions for underwriting automation, claims automation, customer servicing, and risk assessment.
Collaborate with data engineers, MLOps/AIOps, and product teams to ensure robust, scalable, and maintainable solutions.
Contribute to standardization of tools, processes, and best practices.
Adhere to AI/LLM governance, documentation, testing, and other best practices in partnership with key stakeholders.
Present results and recommendations to technical and non-technical audiences, including senior leadership.
Stay current on industry trends, emerging technologies, and best practices in agentic AI, LLMs, and NLP.