About this role
- Partner closely with leaders in Claims and other delivery partners (Insights & Solutions, Technology, and Enterprise Data) to identify AI/ML opportunities and create a delivery roadmap that prioritizes the most impactful work.
- Design, build, and iterate on Machine Learning and Generative & Agentic AI capabilities which deliver real business value for adjusters in Medical and Workers' Compensation claims.
- Collaborate with our partner teams to architect & deliver end-to-end intelligent systems integrating machine learning, LLMs, RAG pipelines, agentic workflows, and structured/unstructured claims data to solve real business problems.
- Apply strong software engineering and ML/AI Ops practices, including object-oriented Python, modular design, test-driven development, and model monitoring.
- Define and implement evaluation and measurement strategies, including impact & acceptance KPIs, human-in-the-loop review, and automated quality metrics.
- Collaborate with Engineers, Product, Architecture, UX, and Claims stakeholders to translate ambiguous problems into working solutions.
- Provide technical mentorship and thought leadership through design reviews and collaboration.
- Expert-level machine learning & statistical modeling practitioner with track record for delivering measurable business value.
- Deep knowledge of insurance claims processes, especially in Workers' Compensation or other medical-driven lines of business (e.g., Medical & Casualty, Disability).
- Experienced in Python development with object-oriented design and engineering best practices.
- Demonstrated AI/ML Ops experience including model lifecycle management, experimentation, evaluation, monitoring, and operational readiness in a cloud-native enterprise environment.
- Demonstrated ability to measure AI/ML and GenAI system quality and business impact using quantitative and qualitative approaches.
- Experience partnering with technical and business stakeholders in complex, enterprise environments.
- Experience delivering ML and AI products through Python API and Application frameworks like FastAPI and Streamlit (or equivalent) Demonstrated experience delivering business value with Generative & Agentic AI in an enterprise setting Building, deploying, and maintaining AI products using leading frontier models from providers like OpenAI, Anthropic, and Google Experience building generative & agentic AI solutions using frameworks like LlamaIndex, LangChain, LangGraph, or equivalent Exposure to CrewAI, AgentCore, or other agentic orchestration frameworks Familiarity with vector databases and embedding-based retrieval systems Deep knowledge of predictive analytic techniques and statistical diagnostics of models.
- Expert knowledge of predictive toolset.
- Demonstrated ability to exchange ideas and convey complex information clearly and concisely.
- Ability to establish and build relationships within and outside the organization.
- Ability to give effective training and presentations to management, executives and other groups.
- Ability to use results of analysis to persuade team, department management or senior management to a particular course of action.
- Deep knowledge of business drivers and market context.
- 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 5 years of relevant experience, a Master`s degree (scientific field of study) and 8 years of relevant experience or may be acquired through a Bachelor`s degree(scientific field of study) and 12 years of relevant experience.