AI Process Optimization Lead - Commercial Insurance
New
US or Ontario, CanadaFull-TimeLead
Salary not disclosed
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Job Details
- Experience
- 5+ years of experience in process improvement, business operations, or consulting - with recent 2 years focused on AI/automation-driven transformation in the insurance industry.
- Required Skills
- PythonSQLMicrosoft Power BITableauMicrosoft Excel
Requirements
- 5+ years of experience in process improvement, business operations, or consulting.
- 2+ years focused on AI/automation-driven transformation in the insurance industry.
- Demonstrated ability to map complex business processes and deliver measurable improvements.
- Experience with LLM-based tools and applications (ChatGPT, Claude, Copilot, or similar).
- Active, daily AI user with experience building custom AI skills/agents and incorporating third-party AI libraries.
- Strong proficiency with data analysis and visualization (SQL, Python, Excel, Tableau/Power BI, or similar).
- Experience defining KPIs and velocity metrics, building measurement frameworks, and driving accountability.
- Excellent communication and stakeholder management skills.
- Experience leading change management for technology adoption across cross-functional teams.
- Self-starter who thrives in a fast-paced, growth-stage environment with ambiguity.
- Bachelor's degree in Business, Engineering, Computer Science, Data Science, or a related field.
Responsibilities
- Embed with business teams (underwriting, claims, wholesale, audits, operations, finance, product) to understand workflows, bottlenecks, and pain points.
- Map end-to-end processes and identify AI automation opportunities, prioritizing by business impact and feasibility.
- Define velocity metrics and set measurable productivity targets for each function.
- Design and implement AI-powered workflow solutions using approved tools to deliver throughput improvements.
- Build and maintain dashboards to track velocity metrics and report progress to leadership.
- Serve as the primary liaison between business teams and engineering, translating business needs into technical requirements.
- Lead change management for AI adoption, including training, documentation, and driving usage.
- Evaluate and recommend AI tools and platforms for the company's approved toolset.
- Support the AI Committee with enterprise-wide velocity reporting, tool approval, and cross-functional best practice sharing.
- Identify opportunities to replicate workflow improvements across product verticals.
- Ensure all AI process solutions meet regulatory obligations (state insurance regulations, HIPAA, CCPA) and data governance standards.
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