Construction Data Specialist

We are looking for a Level 1 Data Tagger to join our Versatile OPS team and support the classification and annotation of crane operations data. This role is critical in ensuring accurate tagging of lifting cycles, which helps enhance AI-driven construction insights. The ideal candidate is detail-oriented, capable of following structured workflows, and comfortable working with digital platforms.

Position Overview

We are looking for a Level 1 Data Tagger to join our Versatile OPS team and support the classification and annotation of crane operations data. This role is critical in ensuring accurate tagging of lifting cycles, which helps enhance AI-driven construction insights. The ideal candidate is detail-oriented, capable of following structured workflows, and comfortable working with digital platforms.

Primary Mission

• Generate the construction data curation, quality assurance, and creation of data sets to the platform environment in the required time and within the required quality
• Escalate to a higher level on demand all abnormal issues with data and platform and recommend the possible solutions path to level 2 specialists
• Do additional data QA and data enrichment for developing the specific and future features on-demand
• Do quality and reliability checks on the construction product components, features, reports, alerts, and insights

Roles and Responsibilities

1. Data Tagging & Classification

• Review and classify lifting cycles based on crane operation footage.Identify and categorize each step in the lifting process (e.g., crane movement, loading, transport, unloading).
• Ensure accurate time tracking and classification of each step.
• Follow predefined tagging guidelines to maintain high data quality standards.

2. Quality Control & Accuracy

• Ensure 100% accuracy in tagging by cross-referencing multiple data points.
• Report unclear or ambiguous cases to team leads for resolution.
• Validate previously tagged data for consistency and correctness.

3. Workflow & Process Adherence

• Work within the Pyramid platform and follow structured workflows.
• Meet daily tagging targets while maintaining accuracy.
• Escalate technical issues or inconsistencies to the team lead.

4. Collaboration & Communication

• Collaborate with team leaders and L2 taggers to improve tagging quality.
• Provide feedback on unclear tagging cases to improve guidelines.
• Participate in training sessions to enhance tagging accuracy.

Required Qualifications and Knowledge

 Technical Skills:

• Experience using digital platforms or data labeling tools (advantage).
• Ability to work with structured tagging guidelines.
• Comfortable using Slack & Jira for reporting.
• Experience with Revit, BIM360, BIM Vision, and AutoCAD.

 Soft Skills:

• Strong attention to detail and ability to follow processes precisely.
• Ability to meet deadlines and maintain a high level of accuracy.
• Proactive mindset—able to escalate unclear cases.

 Preferred Experience:

• Previous experience in data tagging, classification, or annotation.
• Construction knowledge or understanding of crane operations is a plus.
• Basic English (for internal communication & documentation).

Preferred Attributes

• Willing to work in a dynamic start-up environment with fast-paced, frequent changes.
• Willing to work Night shifts to cover different time zones where Versatile Technology is installed.
• Willing to work on off days and holidays if required is an advantage.
• Collaborative and works well in a team environment and with subject matter experts.
• Energetic self-starter with a strong desire to develop, learn and succeed.

Why Join Us?

• Be part of an innovative, AI-driven construction technology company.
• Work in a structured yet dynamic environment with growth potential.
• Gain experience in data operations and digital workflows.
• Full training provided — no prior experience required.
• Schedule — night shifts from 10:00 PM to 6:00 AM.
• Saturdays: part-time depending on the complexity and scope of work.
• Flexible schedule during the training period.
• The position is fully remote.