Analytics Lead, Safety Reporting

About This RoleAI processing…

Key Responsibilities

• 1
  Own the analytical integrity of safety data at Lyft. Set the definitions, inclusion criteria, and reconciliation logic behind every stated figure.
• 2
  Serve as the primary data liaison to external data auditors, ensuring clarity, consistency, and quality of safety data used in external reporting.
• 3
  Maintain documentation standards that ensure continuity across reporting cycles and compliance with reporting requirements.
• 4
  Run the publication cycle end to end: definitions freeze, data lock, QA, leadership review, sign-off. Catch definitional drift before it reaches a published number.
• 5
  Serve as the analytics counterpart to Business, Legal, Policy, and Communications on Safety data.
• 6
  Move safety reporting from volume counts to diagnosis: which categories are growing, where reported incidence diverges from actual, which interventions move outcomes.
• 7
  Own the roadmap for the Trust & Safety reporting portfolio: what gets measured, automated, or retired, and in what order.
• 8
  Set the technical standard for analysts on the safety portfolio: metric definition review, query review, documentation, reproducibility. Mentor junior analysts.
• 9
  Partner with Product, Engineering, Data Science, Business Operations, Legal, and Policy to turn insight into decisions.
• 10
  Develop frameworks and scalable processes to drive decision-making and prioritization
• 11
  Define the metrics used to measure the success of strategic initiatives and health of our support platform; build dashboards to track metrics over time
• 12
  Work closely with cross-functional partners to deliver data-driven insights and actionable recommendations for continuously improving the customer support experience
• 13
  Monitor and diagnose KPI performance and present findings to senior leadership

Requirements

• 5+ years hands-on analytics, including 2+ in trust and safety domain.
• Demonstrated ownership of data used outside the company: filings, transparency reports, audits, or public disclosures.
• Ability to translate unstructured business problems into clearly defined requirements with minimal oversight
• Strong problem-solving and analytical skills with the ability to transition between detailed data and high-level business problems
• Exceptional communication (listening, written, and oral) skills with the ability to present findings & recommendations targeted to the audience in question
• Strong interpersonal skills, with the ability to build relationships and trust across functions and work collaboratively
• Degree in a quantitative field like statistics, economics, applied math, operations research or engineering. Advanced degrees are preferred
• Proficiency in SQL and Python with ability to independently break down large datasets and synthesize inputs from multiple sources

Perks & Benefits