Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.
Waymo’s Product Data Science team works cross-functionally with Engineering, Product and Operations to help the company make the most informed decisions using data. Our team collaborates on high-impact projects across the company — from driving quality and operational efficiency to market analysis and rider satisfaction scores — we help to safely and efficiently scale the Waymo Driver. We are data-driven, curious, open-minded, and adapt quickly to new information.
This role follows a hybrid work schedule and you will report to the Business Intelligence Analyst, Lead.
You will:
- Define and own the canonical metrics for Waymo's growth function: activation, promo redemption, and loyalty; partnering with data engineering to ensure reliable instrumentation and a single source of truth across all stakeholders
- Build and maintain full-funnel performance tracking that give growth leadership real-time visibility from paid media impression through first trip, repeat usage, and retention
- Own paid media tracking infrastructure; taxonomy, channel tagging standards, and end-to-end funnel stitching from campaign to trip;and deliver channel-level performance reporting that drives marketing budget and targeting decisions
- Support the bottom-of-funnel cross functional teams with clean, consistently defined promo performance data
- Serve as the connective tissue between data engineering, data science, marketing, and product; translating business questions into data requirements and proactively surfacing instrumentation gaps before they become decision errors
- Deep dive into business performance
You have:
- 5+ years of experience in a related technical field (or equivalent practical experience), with a proven track record of managing stakeholder relationships and prioritizing multiple projects
- Experience in scripting for automation (e.g. Python) and advanced SQL skills
- Proven experience with data quality principles (accuracy, completeness, consistency) and implementing data validation processes
- Strong communication and stakeholder & management skills, with the ability to convey key insights from complex analysis in summarized business terms, while also being able to effectively communicate with technical teams
- Experience working with the product management and engineering teams
- Experience with data modeling, warehousing and building ETL pipelines
- BS or MS in Computer Science, Data Science, Information System or equivalent
We prefer:
- Experience in the Autonomous Vehicle industry or a strong background in engineering.
- Experience with geospatial data
The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.
Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.
Waymo Mountain View, California, USA Office
1600 Amphitheatre Pkwy, Mountain View, CA, United States, 94043
Waymo San Francisco, California, USA Office
San Francisco, United States
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