Technical Operator- II at Digital Divide Data

Role Overview

• The Operator Level 2 is a senior technical operator responsible for advanced 2D and 3D LiDAR segmentation, quality governance, and operational oversight. This role combines deep technical capability with analytical rigor and end-to-end program accountability. 

Responsibilities

Technical & Quality Oversight

• Conduct advanced-level 2D/3D annotation and segmentation tasks
• Perform structured quality audits
• Identify systemic annotation errors and implement corrective actions

Operational Ownership

• Take end-to-end accountability for program health
• Allocate work effectively across operators
• Ensure achievement of defined team targets: Productivity, Quality, SLA, Efficiency, Utilization
• Ensure strict adherence to process and quality frameworks

Governance & Stakeholder Engagement

• Manage reporting, training, and policy adherence (where no separate POCs exist)
• Interface professionally with global stakeholders
• Manage multiple operational streams concurrently

Experience Requirements

• Minimum 24 months of LiDAR labeling experience
• Demonstrated advanced expertise in 2D and 3D LiDAR annotation and segmentation
• Technical & Analytical Competencies

Advanced LiDAR & Segmentation Expertise

• Advanced capability in complex 3D point cloud segmentation
• Multi-class object classification
• Handling occlusions and edge-case annotation scenarios
• Precise cuboid alignment and spatial calibration

Tools & Systems

• Proficient in MS Office or Google Suite
• Working knowledge of JIRA or ticketing systems

Advanced Excel / Google Sheets capability, including:

• Pivot tables
• VLOOKUP
• Data extraction and manipulation
• Analytical & Root Cause Capability
• Data-driven performance analysis

Application of:

• Root Cause Analysis (RCA)
• Understanding of operational metrics:
• Shrinkage
• Utilization
• Productivity
• SLA adherence
• Application of detailed ontology and taxonomy standards
• Reviewing and correcting segmentation inconsistencies
• Identifying systemic annotation error patterns

Qualifications

Education Requirements

Diploma or higher qualification in a relevant field such as:

• Computer Science
• Information Technology
• Engineering (Computer, Electrical, Geospatial, Robotics, or related)
• Data Science or Analytics
• Geospatial or Remote Sensing disciplines
• Or equivalent technical discipline