Evaluates and quality-controls legal AI skills, workflows, and use cases; researches prompting and applied AI methods; develops best-practice exemplars; tests new product capabilities; trains Legal Engineers; supports executive demonstrations; coordinates global skills libraries; and contributes approximately 30% of time to live client work.

Turn data into product and business decisions through metric definition, experimentation, causal analysis, deep-dive research, and clear recommendations. Model reliable analytical data in dbt, build scalable dashboards and reporting, partner with data engineering, and influence leaders across Product, Finance, Growth, GTM, and Customer Success. The role also helps establish data-team standards, tooling, and operating practices in an AI-first environment.

Design and run mixed-methods studies measuring legal teams' real AI proficiency; build and validate surveys/interview protocols; analyze usage and outcome data; translate findings into product, onboarding, and enablement recommendations; communicate results via reports, presentations, and dashboards; prioritize future research.