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7 days ago
As a skilled Python AI engineer, you will develop intelligent frameworks for synthetic and automated test data generation to support clinical trials, regulatory submissions, and GxP-compliant systems.
Key Responsibilities- Create Python frameworks to produce synthetic clinical and operational datasets, generating CDISC-compliant datasets (SDTM, ADaM) for data transformation, analysis, and reporting workflows.
- Apply generative AI techniques to model realistic clinical scenarios, creating synthetic patient journeys across EDC, eCOA, CTMS, LIMS, and PV systems.
- Maintain adherence to industry standards, implementing anonymization/obfuscation while preserving clinical and statistical fidelity.
- Demonstrate strong expertise in Python programming, including pandas, NumPy, scikit-learn, PyTorch/TensorFlow, and LangChain libraries.
- Have hands-on experience generating synthetic clinical data or applying CDISC standards (SDTM, ADaM, Define-XML).
- Be familiar with clinical data management systems, such as Medidata Rave, Veeva CDB, Oracle InForm, and others.
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