Data Scientist, Agentic AI

Data Scientist, Agentic AI - Insurance Underwriting

Location: 3 days in office - New York, Boston, Bethlehem, Holmdel

We are seeking a Data Scientist, Agentic AI—an experienced individual contributor with strong expertise in agentic AI, LLMs, and NLP, and a proven ability to translate advanced research into impactful enterprise solutions. This role focuses on designing, deploying, and scaling agent-based systems and LLM-powered applications that modernize workflows, enhance decision-making, and support business growth. You will collaborate directly with senior leaders on high-visibility initiatives that bring next-generation AI to life across the organization.

You Will

• Design and implement agentic AI solutions that automate workflows, enhance decisions, and improve customer and employee experiences.
• Apply LLMs and generative AI to analyze unstructured data such as contracts, underwriting notes, claims, medical documentation, and customer interactions.
• Build autonomous agents and multi-step reasoning systems that integrate with enterprise platforms and deliver measurable outcomes.
• Collaborate with data engineers and AIOps teams to ensure models and systems are scalable, resilient, and production-ready.
• Translate research in agentic AI, reinforcement learning, and LLM architectures into practical applications for underwriting, claims automation, customer service, and risk analysis.
• Work closely with product, engineering, and business stakeholders to define use cases, shape solutions, and evaluate impact.
• Contribute to the Data Science Lab by developing reusable components, frameworks, and best practices for building agentic AI systems.
• Follow governance standards for AI and LLM development, including documentation, testing, and model risk management.

You Are

• Passionate about applying advanced AI—especially agentic AI, LLMs, and NLP—to solve meaningful business problems.
• Curious about autonomous systems and next-generation AI architectures that transform industries.
• A hands-on builder who enjoys taking solutions from prototype to production.
• Effective in cross-functional environments, aligning technical implementation with business goals.

You Have

• PhD with 0–1 years, Master’s with 2 years, or Bachelor’s with 4 years of experience in Computer Science, Engineering, Statistics, Applied Mathematics, or a related field.
• Experience in the insurance industry (underwriting experience preferred).
• 2 years of hands-on experience in AI/ML modeling and development.
• Solid foundation in probability, statistics, and machine learning fundamentals.
• Strong Python programming skills and experience with frameworks such as PyTorch, TensorFlow, and LangGraph.
• Experience building LLM-powered systems, generative AI applications, and multi-step reasoning pipelines.
• Excellent analytical and problem-solving skills with strong attention to detail.
• Strong communication skills and proven ability to collaborate with product and engineering teams.
• Working knowledge of software engineering best practices (Git/GitHub, testing, logging).
• Familiarity with a wide range of ML techniques (classification, clustering, decision trees, boosting/bagging, neural networks) and their practical trade-offs.