New Grad Data Quality Manager for AI Systems

Hire Feed; Pakistan; On-site; PKR 1,674,000 - 2,790,000; Full time

Job summary

Hire Feed is hiring a Human Data Manager, New Grad on a full-time basis in Pakistan. You will ensure accuracy and integrity of data used in AI/ML models by performing quality checks, correcting errors, and validating outputs. Collaborate with cross-functional teams to maintain datasets powering automated systems.

The role emphasizes data annotation, labeling, QA processes, and clear reporting of data issues, supporting responsible data practices and model accuracy.

Qualifications

• Bachelor’s degree in Computer Science, Data Science, or a related field.
• Familiarity with data annotation, labeling, or quality assurance processes.
• Experience with spreadsheets, databases, or data visualization tools.
• Strong attention to detail and ability to spot discrepancies in large datasets.
• Proficiency in written and verbal communication for reporting issues and solutions.

Responsibilities

• Perform manual reviews of AI-generated data to identify inaccuracies, inconsistencies, or biases
• Correct and annotate data points to improve model performance and reliability
• Validate datasets against predefined quality criteria and business requirements
• Document data issues and resolutions for future reference and team transparency
• Communicate findings and recommendations to engineering and product teams

Skills

Data annotation

Data labeling

Quality assurance

Attention to detail

Communication skills

Education

Bachelor's degree in Computer Science, Data Science, or a related field

Tools

Spreadsheets

Databases

Data visualization tools

Job description

Hire Feed is hiring a Human Data Manager, New Grad on a full-time basis in Pakistan. You will ensure accuracy and integrity of data used in AI/ML models by performing quality checks, correcting errors, and validating outputs. Collaborate with cross-functional teams to maintain datasets powering automated systems.

The role emphasizes data annotation, labeling, QA processes, and clear reporting of data issues, supporting responsible data practices and model accuracy.