Compliance Analyst

Uber Uber · Consumer · Taipei City, Taiwan · Safety, Security & Insurance

This role is a QA analyst for Uber's Global Public Safety team, focusing on reviewing law enforcement data requests and responses to ensure compliance with policies and data privacy standards. The analyst will perform manual reviews, identify discrepancies, resolve issues, and contribute to reporting and process improvements.

What you'd actually do

  1. Evaluate and review law enforcement data requests to ensure responses are consistent with internal policy and processes.
  2. Execute quality assurance checks on work performed by the broader global PSRT team, identifying discrepancies in legal process validation, contact authentication, data investigations and suspected offender management.
  3. Analyze and problem solve for issues identified during the quality assurance process, including escalating to a team lead for review, suggesting corrective actions in both agent performance, internal processes and solutions at scale.
  4. Utilize internal tools to track QA findings and contribute to dashboards that provide agent performance feedback.
  5. Under supervision, collaborate with cross-functional teams to identify improvements to standards and processes within the Public Safety Response Team.

Skills

Required

  • 2+ years of relevant work experience
  • Experience with privacy and/or public safety
  • Basic understanding of handling confidential information
  • Appreciation for data protection
  • Skilled in various computer systems and software, including Salesforce, Jira, and Google Suite
  • Ability to clearly respond to policy questions
  • Ability to document findings both in writing and through thorough record keeping

Nice to have

  • Basic knowledge of business models, products, and privacy policy
  • Basic understanding of the legal and regulatory frameworks within the area of responsibility
  • Demonstrated interest in law enforcement, international affairs, or security
  • Experience working within structured business models or high-volume ticket environments