Data Specialist

Role Overview

We are recruiting a Human Data Manager, suitable for new graduates, to join our client's team on a full-time remote basis. The primary focus is on managing and maintaining accurate, high-quality datasets used for AI model training and evaluation. The role demands vigilance in ensuring the precision and relevance of labeled data and contributing to enhancing data annotation workflows tailored for machine learning projects.

Primary Responsibilities

• Examine and verify human-labeled datasets to guarantee consistency and correctness for AI training purposes.
• Detect and address inconsistencies in data annotations through careful cross-referencing with original source documents and established guidelines.
• Work collaboratively across departments to update and refine annotation standards and boost the quality of datasets.
• Track and report key metrics related to data labeling performance, analyzing trends and outcomes.
• Support thorough documentation of procedures, data sources, labeling rules, and quality control measures.

Qualifications

• Prior experience in data annotation, labeling, or quality assurance is advantageous.
• Strong attention to detail and familiarity with fundamental data validation techniques for reviewing datasets.
• Capability to adhere to structured guidelines ensuring consistent data processing.
• Basic knowledge of AI and machine learning principles, especially regarding the critical role of training data quality.
• Competency in using spreadsheets or comparable data management applications for organizing and tracking information.

Opportunity Details

This position offers a chance to engage with a leading organization in the Technology and Information sector, playing a vital part in developing dependable AI systems through meticulous data stewardship. It provides practical exposure to the integration of data within real-world machine learning workflows.

Equal Employment Opportunity Statement

We promote an inclusive hiring process, welcoming all applicants with the requisite skills and experience. Application evaluations focus exclusively on technical expertise and qualifications, independent of candidates’ background or past employment.