Quickhyre ai
Privacy Analyst - Data Protection
- Remote
India, भारत
Vacancy description
Recruitment Room
$ 59520 p.a.
भारत
Employment Type: Contractor
Work Arrangement: Remote
Hourly Rate: $31–$60 per hour
Annualized Full-Time Equivalent: $59,520–$115,200 per year
The annualized figure is based on 40 hours per week and 48 working weeks per year. Actual earnings depend on project availability, tasks completed, and hours worked.
We are seeking detail-oriented Data Privacy Analysts to review transformed datasets and verify that personally identifiable information (PII) has been properly redacted or anonymized.
In this remote contract role, you will conduct document reviews and quality spot-checks to identify sensitive information that may have been missed or inadequately protected. You will document discrepancies, assess privacy handling, and provide clear feedback to support accurate and consistent data protection practices.
This opportunity is suited to professionals with experience in data privacy, legal document review, eDiscovery, compliance, or quality assurance who can handle sensitive information with precision and discretion.
Conduct spot-checks of transformed datasets to verify that PII has been appropriately redacted or anonymized.
Review documents and datasets for sensitive information that may remain exposed.
Identify instances of incomplete, inconsistent, or incorrect redaction and anonymization.
Assess whether privacy handling meets the standards and guidelines provided for the project.
Perform detailed document reviews to verify consistent application of data privacy requirements.
Check transformed records for accuracy and completeness.
Identify discrepancies and potential privacy risks requiring further review.
Provide clear, actionable feedback on errors and areas requiring correction.
Document review findings, discrepancies, and observations using designated tools and templates.
Maintain accurate and consistent review records.
Communicate findings clearly to support follow-up and quality improvements.
Handle sensitive information responsibly throughout the review process.
Strong understanding of personally identifiable information (PII) and data privacy principles.
Experience reviewing documents, datasets, or records for accuracy, completeness, or compliance.
Strong attention to detail when identifying sensitive information and reviewing redaction or anonymization.
Ability to conduct systematic spot-checks and document findings accurately.
Analytical skills and sound judgment when assessing potential privacy issues.
Ability to provide clear, actionable written feedback.
Discretion and professionalism when handling sensitive or confidential information.
Experience in contract review, quality assurance, eDiscovery, or compliance processes.
Knowledge of data privacy regulations and information governance practices.
Professional background as a Paralegal, eDiscovery Specialist, Privacy Analyst, Information Governance Specialist, Compliance Manager, or Legal Document Review Lead.
Experience in legal document review, litigation support, or managed legal services.
Demonstrated experience working with sensitive data in high-stakes environments.
Ability to maintain accuracy and consistency under time pressure.
Data Privacy
Personally Identifiable Information (PII)
PII Redaction
Data Anonymization
Document Review
Dataset Validation
Quality Assurance
Spot Checks
eDiscovery
Legal Document Review
Information Governance
Compliance Review
Privacy Risk Identification
Discrepancy Reporting
Attention to Detail
Analytical Thinking
Written Communication
Confidential Data Handling
This is a remote, hourly contract opportunity focused on data privacy review and quality assurance.
You will review transformed datasets, verify the handling of sensitive information, conduct targeted spot-checks, and document findings using the tools and templates provided. Consistency, discretion, and adherence to project guidelines are essential.
Success means accurately identifying PII that has not been properly redacted or anonymized, documenting discrepancies clearly, and consistently applying privacy review standards.
Your work should help improve dataset quality, reduce the risk of sensitive information exposure, and support reliable data privacy practices.
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