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Technical Operator- II at Digital Divide Data

Digital Divide Data
Full-time
On-site
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