Manager Compliance
BeOne
- Drive cross-functional R&D initiatives from planning through delivery, managing scope, timelines, milestones, dependencies, and outcomes with focus on AI integration and optimization strategies.
- Identify and track project risks, issues, and action plans ensuring timely resolution, escalation, and stakeholder alignment; monitor AI model performance and accuracy metrics for compliance in regulated environments.
- Drive collaboration across R&D and Technology teams to deliver process improvements, system enhancements, automation, AI-driven solutions, and new capabilities aligned with regulatory requirements.
- Establish project KPIs including AI usage and accuracy metrics, dashboards, RAID logs, status reporting, and governance routines to support leadership decisions and ensure AI auditability.
- Coordinate stakeholders across R&D functions, facilitate planning and decision-making on AI tool adoption and implementation, manage priorities and dependencies, and drive teams toward successful delivery.
- Work independently and with global teams, covering extended hours to support U.S. Eastern time collaboration; provide technical training and consultation on Generative AI mechanics and defensibility.
- Designed and implemented client-specific solutions supporting complex litigation and investigation workflows across the full eDiscovery reference model.
- Demonstrated extensive knowledge of legal case management systems and litigation lifecycle through end-to-end product strategy and delivery.
- Communicated advanced ML concepts including model drift and hallucination risks to C-Suite and client audiences in clear, non-technical business language.
- Analyzed off-the-shelf eDiscovery and AI tools to evaluate capabilities and make recommendations for new platform offerings and implementations.
- Explained confidence scoring and related AI model uncertainty metrics to stakeholders to ensure defensible deployment of predictive algorithms.
- Acted as Subject Matter Expert in direct client consultations, explaining AI mechanics, defensibility, and limitations to build trust and drive adoption.