Remote Data Security & DLP Analyst - AI Training

Alignerr Corp.; Paris; Remoto; EUR 83.000 - 165.000; Part-time

Descrizione del lavoro

Alignerr is hiring a Data Security & DLP Analyst to help train frontier AI systems by applying real-world data protection expertise. The role focuses on understanding how data leaks occur and how to stop them, shaping AI reasoning about sensitive information risk.

The remote hourly contract involves analyzing security scenarios, classifying sensitivity, and evaluating prevention, detection, and incident response strategies to ensure AI training datasets are robust and compliant with privacy

Competenze

• 2+ years of experience in data security, compliance, or security operations.
• Hands-on familiarity with DLP tools, data classification frameworks, and privacy or regulatory concepts (e.g., GDPR, HIPAA, CCPA)
• Practical understanding of how data risk surfaces in modern enterprise and cloud environments
• Able to think through edge cases, ambiguous scenarios, and realistic threat patterns
• Strong written communication — you can clearly explain your reasoning

Mansioni

• Analyze realistic data security and DLP scenarios across cloud, SaaS, and enterprise environments
• Classify data sensitivity levels, exposure paths, and policy violations
• Evaluate prevention, detection, and incident response strategies for accuracy and completeness
• Generate, label, and validate data security cases used to train and benchmark AI systems
• Provide expert judgment on how sensitive information risk plays out in real-world contexts

Conoscenze

Data security

Compliance

Security operations

Edge-case reasoning

Written communication

Strumenti

DLP tools

Data classification

Descrizione del lavoro

Alignerr is hiring a Data Security & DLP Analyst to help train frontier AI systems by applying real-world data protection expertise. The role focuses on understanding how data leaks occur and how to stop them, shaping AI reasoning about sensitive information risk.

The remote hourly contract involves analyzing security scenarios, classifying sensitivity, and evaluating prevention, detection, and incident response strategies to ensure AI training datasets are robust and compliant with privacy