Purpose:

This function supports the protection of patient privacy when clinical trial data is shared externally.

Typical use cases:

- Regulatory submissions
- Data sharing with researchers
- Health authority requests
- External collaborations
- Clinical trial transparency initiatives

Typical responsibilities:

- Review datasets for personally identifiable information (PII).
- Apply anonymization methodologies.
- Remove or mask sensitive variables.
- Assess re-identification risk.
- Create anonymized SDTM and ADaM datasets.
- Produce anonymization reports and documentation.
- Validate anonymized outputs.

Key technical skills:

1. SAS programming.
2. SDTM and ADaM expertise.
3. Clinical trial disclosure processes.
4. Metadata and standards expertise.
5. Knowledge of data privacy regulations:

- GDPR
- HIPAA
- EMA Policy 0070

Ideal profile:

- Clinical programming teams.
- Regulatory programming.
- Clinical disclosure teams.
- Data transparency functions.
- 4+ Years of relevant experience

Success factors:

- Meticulous attention to detail
- Robust compliance mindset
- Understanding of patient privacy regulations
- Process-oriented approach
- Ability to work within heavily governed environments

📌 Statistical Programmer (Data Anonymization) (India)
🏢 Veramed
📍 India