AI Operations Specialist
HybridChicago, Illinois, United States or New York, United States
Job Summary
Identify, prioritize, and champion high-impact AI use cases across the reinsurance value chain by translating operational pain points into scalable solutions. Execute AI strategy for reinsurance broking operations by partnering with Broking, Distribution, Analytics, CSS/Operations, and IT to deliver generative AI solutions from ideation through production. Coordinate cross-functional teams to ensure strong execution discipline and adoption while establishing best practices for responsible AI governance and model risk. Drive change management initiatives through training materials and communities of practice to accelerate capability-building. This role requires 8–10 years of experience in process re-engineering or AI/ML, with a hybrid schedule of at least three days in the office.
Required Qualifications
- 8–10 years of experience in process re-engineering, data science, AI/ML, product management, strategy, operations consulting, or related experience
- Deep technical expertise in machine learning and generative AI (LLMs, prompt engineering, RAG) with hands-on implementation experience
- Familiarity with MLOps practices and tools
- Proven track record translating business problems into AI use cases and delivering measurable value in financial services, insurance, or reinsurance
- Exceptional stakeholder management, influencing, and communication skills, including ability to build consensus and drive change with senior leaders
- This is a hybrid role that has a requirement of working at least three days a week in the office
- All Marsh colleagues are expected to be in their local office or working onsite with clients at least three days per week
Desired Qualifications
- Product management experience defining product vision, managing roadmaps, prioritizing features, and launching successful solutions with strong execution delivery
- Experience implementing AI solutions for (re)insurance workflows, including familiarity with reinsurance analytics tools and/or catastrophe modeling platforms (RMS, AIR, CoreLogic)
- Advanced degree (Master's/PhD) and/or relevant professional certifications in AI/ML, product management, or insurance qualifications (e.g., ACAS, FCAS, CII)
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