Data Analyst | $45/hr | Remote

The Ai Training Company; España; Remote; EUR 42,000 - 64,000; Full time

Job summary

The Ai Training Company is seeking experienced Data Analysts and Data Governance professionals for a remote AI training project focused on large-scale business data. You will review, validate, and quality-check datasets and documents while ensuring privacy and PII requirements.

Ideal candidates bring data analysis, data quality, and document review experience and are comfortable working independently in a distributed, remote environment.

Qualifications

• Professional experience in data analysis or data governance
• Experience reviewing large datasets and sensitive information
• Strong attention to detail and documenting findings clearly

Responsibilities

• Review and analyze large business datasets
• Validate data for accuracy, completeness, consistency, and relevance
• Identify data quality issues, duplicates, anomalies, and missing values
• Apply data privacy and PII-handling requirements
• Document data-quality issues and provide recommendations
• Communicate findings to project stakeholders

Skills

Data analysis

Attention to detail

Documentation

Communication

Privacy awareness

Tools

Excel

SQL

Python

Tableau

Power BI

Job description

Data Analysts, Data Quality & Business Data Review Specialists. Remote AI Project

We are seeking experienced Data Analysts, Business Data Analysts, Data Quality Specialists, Data Reviewers, and Data Governance Professionals to support a high-impact AI training project focused on large-scale business data.

You will review, analyze, validate, and quality-check datasets and documents while ensuring strict adherence to privacy, security, and personally identifiable information (PII) requirements.

What You’ll Do

• Review and analyze large business datasets
• Validate data for accuracy, completeness, consistency, and relevance
• Identify missing values, duplicate records, anomalies, and incorrect data
• Review documents containing structured and unstructured business information
• Apply strict data privacy and PII-handling requirements
• Identify and flag sensitive or personally identifiable information
• Perform data validation and quality assurance checks
• Investigate data inconsistencies and determine likely root causes
• Document data-quality issues clearly
• Provide recommendations to improve data accuracy and integrity
• Apply project-specific quality standards and review guidelines
• Contribute to the improvement of QA processes, checklists, and evaluation criteria
• Communicate findings clearly to project stakeholders
• Maintain compliance with privacy, security, and data-handling requirements
• Work independently in a remote, distributed project environment

Who Can Apply

Relevant backgrounds include:

Data Analysts, Senior Data Analysts, Business Data Analysts, Business Analysts, Data Quality Analysts, Data Quality Specialists, Data Review Analysts, Data Validation Analysts, Data Integrity Analysts, Data Operations Analysts, and Data Management Analysts.

We also welcome:

Quality Analysts, Quality Assurance Analysts, QA Analysts, Data QA Specialists, Data Auditors, Data Reviewers, Quality Reviewers, Quality Control Analysts, QC Analysts, and Data Accuracy Specialists.

Data governance and privacy backgrounds may include:

Data Governance Analysts, Data Governance Specialists, Data Privacy Analysts, Privacy Operations Specialists, Information Governance Analysts, Data Compliance Analysts, Data Stewardship Professionals, Data Stewards, and Information Management Specialists.

Business and operations backgrounds may include:

Operations Analysts, Business Operations Analysts, Process Analysts, Reporting Analysts, Research Analysts, Risk Analysts, Compliance Analysts, Audit Analysts, and Business Intelligence Analysts with strong data-review experience.

Document-review backgrounds may include:

Document Review Specialists, Document Analysts, Records Analysts, Information Management Specialists, Documentation Specialists, Compliance Reviewers, Audit Reviewers, and Quality Assurance Reviewers.

AI and evaluation backgrounds may include:

AI Data Analysts, AI Evaluators, Data Annotators, Data Labelers, Human Feedback Specialists, Model Evaluators, AI Quality Analysts, Annotation Quality Specialists, and Rubric Evaluators.

Relevant Data Analysis Experience

Strong candidates may have experience with:

• Data cleaning
• Data validation
• Data profiling
• Data quality assessment
• Data integrity checks
• Anomaly detection
• Data matching
• Record linkage
• Data transformation
• Data verification
• Data classification
• Data annotation
• Data review

Requirements

• Professional experience in data analysis, data quality, document review, business analytics, data governance, QA, audit, or a closely related field
• Demonstrated ability to work with large business datasets
• Experience identifying data errors and inconsistencies
• Strong attention to detail
• Ability to review sensitive information carefully
• Understanding of data privacy and PII-handling principles
• Strong analytical and problem-solving skills
• Ability to clearly document findings and recommendations
• Strong written and verbal communication
• Ability to follow detailed quality and privacy guidelines
• Comfortable working independently in a remote environment
• Consistent and reliable delivery of high-quality work

Preferred Background

• Experience working with personally identifiable information
• Experience with sensitive or confidential business data
• Experience with document review
• Experience in data quality assurance
• Experience with privacy compliance or data governance
• Experience building or applying data-quality standards
• Experience reviewing work produced by other analysts
• Experience using Excel, SQL, Python, Tableau, or Power BI
• Experience with CRM, finance, operations, or customer datasets
• Experience creating SOPs, checklists, or QA processes

This opportunity is ideal for professionals who can look at a large dataset or collection of documents and quickly identify what is missing, inconsistent, inaccurate, sensitive, or potentially risky, then document the issue clearly and help improve overall data quality. We are a referral partner of the client.