Analytics Lead, Safety & Customer Care

Lyft Lyft · Consumer · New York, NY +1 · SCC Analytics

Lyft is seeking an Analytics Lead for their Safety & Customer Care team. This role will partner with cross-functional stakeholders to identify opportunities and design solutions for improving the customer support experience. The lead will leverage analytical expertise to deliver actionable insights and recommendations, drive quality business decisions, and lead within the Support organization. Responsibilities include developing frameworks, defining metrics, building dashboards, designing A/B tests, and monitoring KPI performance. Requires 5+ years of technical experience in a data science or analytical role, proficiency in SQL and Python, and strong problem-solving and communication skills.

What you'd actually do

  1. Partner with Product, Engineering, Data Science & Analytics, Business Operations and other cross-functional stakeholders to achieve business goals
  2. Develop frameworks and scalable processes to drive decision-making and prioritization
  3. Define the metrics used to measure the success of strategic initiatives and health of our support platform; build dashboards to track metrics over time
  4. Design A/B tests and execute analyses to evaluate the impact of new product features and operational improvements
  5. Work closely with cross-functional partners to deliver data-driven insights and actionable recommendations for continuously improving the customer support experience
  6. Monitor and diagnose KPI performance and present findings to senior leadership

Skills

Required

  • SQL
  • Python
  • Data Analysis
  • A/B Testing
  • Dashboarding
  • KPI Definition
  • Problem Solving
  • Communication

Nice to have

  • Advanced degrees in quantitative fields
  • Experience in a data science role or equivalent analytical role in a high growth startup

What the JD emphasized

  • 5+ years of hands-on technical experience in a data science role or equivalent analytical role in a high growth startup
  • Proficiency in SQL and Python with ability to independently break down large datasets and synthesize inputs from multiple sources