
Intelligent Test Data Engineer
2 days ago
Job Description
">We are seeking a skilled professional to design and implement intelligent frameworks for synthetic and automated test data generation. This role will leverage AI/ML and Python automation to deliver high-quality, audit-ready datasets that reduce reliance on production data, accelerate testing cycles, and ensure compliance with regulatory standards.
">Key Responsibilities
">- Build Python frameworks to generate synthetic clinical and operational datasets.
- Produce compliant datasets for transformation, analysis, and reporting workflows.
- Simulate domain-specific datasets with variability and referential integrity.
- Develop connectors for validation and statistical programming workflows.
AI/ML in Data Generation
">- Apply generative AI to model realistic clinical scenarios.
- Create synthetic patient journeys across systems.
- Use AI-driven automation to simulate rare or complex cases.
Compliance & Data Governance
">- Ensure adherence to regulatory standards.
- Implement anonymization while maintaining clinical and statistical fidelity.
- Produce validation protocols and documentation.
Required Skills & Qualifications
">- Strong Python expertise (pandas, NumPy, scikit-learn, PyTorch/TensorFlow).
- Familiarity with CDISC standards (SDTM, ADaM) and clinical data management systems.
- Knowledge of regulated data handling and GxP/21 CFR Part 11.
- Experience with test automation frameworks and validation tools.
Preferred Qualifications
">- Background supporting clinical trial systems.
- Understanding of statistical workflows and integration into test pipelines.
- Cloud experience for secure AI/ML deployment.
- Experience with inspection readiness and validation documentation.
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