
AI Engineer for Synthetic Data Generation
2 days ago
Job Title: Python AI Engineer for Clinical Data Generation
Description: We are seeking a skilled Python AI Engineer to join our team in designing and implementing intelligent frameworks for synthetic and automated test data generation in support of clinical trials, regulatory submissions, and GxP-compliant systems.
Key Responsibilities:
- Create Python frameworks to generate synthetic clinical and operational datasets with high-quality, audit-ready outputs.
- Develop CDISC-compliant datasets (SDTM, ADaM) for data transformation, analysis, and reporting workflows.
- Synthesize domain-specific datasets (adverse events, labs, demographics, drug exposure) with variability and referential integrity.
- Build connectors for Define-XML, Pinnacle21 validation, and statistical programming workflows.
AI/ML Applications:
- Apply generative AI (LLMs, GANs, diffusion models) to model realistic clinical scenarios and create synthetic patient journeys across EDC, eCOA, CTMS, LIMS, and PV systems.
- Use AI-driven automation to simulate rare or complex cases for stress and edge-case testing.
Compliance and Governance:
- E nsure adherence to GxP, 21 CFR Part 11, HIPAA, and GDPR standards for data handling and storage.
- Implement anonymization/obfuscation techniques while maintaining clinical and statistical fidelity.
- Produce validation protocols and documentation for audit and inspection readiness.
Required Skills and Qualifications:
- Strong expertise in Python programming language (pandas, NumPy, scikit-learn, PyTorch/TensorFlow, etc.).
- Hands-on experience generating synthetic clinical data or applying CDISC standards (SDTM, ADaM, Define-XML).
- Familiarity with clinical data management systems (Medidata Rave, Veeva CDB, Oracle InForm, etc.).
- Knowledge of GxP/21 CFR Part 11 and regulated data handling.
- Experience with test automation frameworks (PyTest, Robot Framework) and validation tools (Pinnacle21).
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