Efficient, under budget global sensor deployment for Uber

Project Summary

Managed the deployment and operation of proprietary vehicle mounted sensors collecting 360 degree imagery, lidar, and location data used in base map production, ground truth identification for ML model training, and autonomous vehicle navigation. Operations spanned 5 continents, requiring the deployment of sensors and training personnel across timezones and borders, as well as overseeing the staffing and training of local drivers.

The Role

• Staff and manage vendor team responsible for establishing and operating Uber’s geospatial sensor deployment, data acquisition and production workflows.
• Develop acquisition strategy by optimizing client’s market priorities and collection windows dependent on seasonally viable latitudes.
• Establish overall project budget broken down by AOI based on KMs to collect, terrain, and seasonality, dictating resource requirements, costs, and timelines.
• Design end to end org chart and identify key personnel to fulfill functional requirements such as: logistics, dispatch, hardware support, city launch, and imagery QC.   
• Manage international personnel and asset deployment, ensuring compliance with international visa and customs requirements. 
• Track and report on team performance against data acquisition rates and budget metrics.
• Make final staffing decisions (hiring, allocation, firing).
• Contribute to and sign off on SOPs. 
• Provide stakeholders with monthly and quarterly business reviews.  

Responsibilities

• Manage Vendors
• Project Budgeting
• Personnel & Asset Deployment
• Staffing
• SOP Creation & Reporting

The Results

We deployed hundreds of sensors across 5 continents on time and under budget, reducing the cost per KM for each subsequent deployment by an average of 5%.

Met all data acquisition targets by maintaining sensor utilization rates of >98% during viable collection hours.