
Python AI Engineer – Synthetic Data Developer
7 days ago
Job Overview:
This exciting role involves developing and implementing cutting-edge frameworks for the creation of synthetic test data in support of clinical trials, regulatory submissions, and GxP-compliant systems. The ideal candidate will possess a strong background in Python programming and expertise in generating synthetic clinical data or applying CDISC standards.
Key Responsibilities:
- Design and build advanced Python frameworks to generate synthetic datasets for clinical trials.
- Develop CDISC-compliant datasets (SDTM, ADaM) for data transformation, analysis, and reporting workflows.
- Simulate domain-specific datasets with variability and referential integrity, ensuring accuracy and reliability.
- Collaborate with cross-functional teams to integrate test data generation into CI/CD pipelines, trial simulations, and automated validation environments.
Required Skills & Qualifications:
- Strong Python programming skills, including experience with pandas, NumPy, Scikit-Learn, PyTorch/TensorFlow, and LangChain.
- Familiarity with clinical data management systems, such as Medidata Rave, Veeva CDB, Oracle Informatics, and CDISC standards.
- Hands-on experience with test automation frameworks, validation tools, and inspection readiness documentation.
Preferred Qualifications:
- Background supporting clinical trial systems, including EDC, CTMS, PV, LIMS, and ECOA.
- Understanding of statistical workflows and integration into test pipelines.
- Cloud experience with secure AI/ML deployment on platforms like AWS, Azure, and GCP.
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