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Data Quality Specialist

  • On-site
    • National Capital Region, Philippines

Short-term, project-based role focused on data quality and accuracy

Job description

Job Summary

KDCI Outsourcing is seeking a Data Quality Specialist to support a short-term data research

and cataloging project focused on verifying and correcting company enrichment data for CMS

ingestion of companies. The role involves manual data entry, categorization, and basic data

cleanup to ensure information is organized and structured for internal use. Candidates should

be comfortable working with online sources and basic AI tools while maintaining accuracy and

confidentiality when handling sensitive project data.

Key Responsibilities

Data Collection & Entry

• Use provided tools to research and compile information into a master list.

• Ensure that data is complete, organized, and categorized correctly based on set

guidelines.

Data Processing & Cleanup

• Perform data cleanup and formatting to ensure usability of the dataset.

• Identify and resolve data quality issues such as duplicate entries, irrelevant entries,

missing required fields, and inconsistent formatting across records.

Visual Asset QA

• Image quality review using a custom app and a content management system to verify

and update assets to meet quality requirements.

Confidentiality & Compliance

• Handle confidential information responsibly and maintain strict data privacy standards.

• Follow internal protocols for secure data handling and storage.

Job requirements

Job Requirements

• Experience in data entry, data research, or administrative data processing.

• Strong attention to detail and comfortable performing manual data entry and data

categorization tasks.

• Comfortable using AI-assisted research tools, verifying information across multiple web

sources, and exercising judgment when data is ambiguous or incorrect.

• Must be able to handle confidential data responsibly.

• Basic proficiency in Google Sheets, Excel, or similar tools.

• Able to work onsite and meet output-based performance expectations.

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