Metric Governance & Foundations:
Drive governance for Safety’s most critical metrics, including Incident Rate and leading indicators of safety risk. Recommend durable definitions, inclusion/exclusion logic, auditability, lineage, and consistency over time. Ensure metric frameworks remain credible as the platform, product, and risk landscape evolve.
Data Quality & Measurement Integrity:
Serve as Safety’s measurement steward - lead end-to-end accountability for the quality and reliability of safety data. Partner with DS / Eng / Ops to resolve issues, and establish clear monitoring and escalation mechanisms that improve trust in reported safety outcomes.
Analytical Investigation, Insight Generation & Business Translation:
Lead deep dives into performance shifts, emerging risks, and measurement anomalies, combining quantitative analysis with operational context to identify what is happening, why it is happening, and what Safety should do next; then turn those insights into crisp, credible narratives that help leaders make decisions, prioritize investments, and communicate clearly to senior stakeholders.
AI-Enabled Insights & Scalable Workflows:
Define and advance the future state of Safety analytics by identifying opportunities to automate recurring analysis, improve self-serve access, and use AI-enabled workflows to accelerate insight generation without compromising rigor
Safety Ops Enablement:
Enable Safety Operations and regional partners to use trusted safety metrics consistently and effectively. Build or shape dashboards, reporting tools, education materials, and analytical resources that improve understanding, speed up decision-making, and strengthen stakeholder influence.
Reporting & Decision Support:
Ensure executive- and external-facing reporting is rigorous, defensible, and efficient, with clear underlying methodology and a consistent measurement framework.