Python ai engineer – synthetic test data

2 weeks ago

Varanasi, India Saxon Global Full time

Python AI Engineer – Synthetic Test Data (Life Sciences / Gx P)About the RoleWe are seeking a Python AI Engineer to design and implement intelligent frameworks for synthetic and automated test data generation in support of clinical trials, regulatory submissions, and Gx P-compliant systems. 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 FDA, EMA, and global regulatory standards.Key Responsibilities???? Synthetic Test Data AutomationBuild Python frameworks to generate synthetic clinical and operational datasets.Produce CDISC-compliant datasets (SDTM, ADa M) for data transformation, analysis, and reporting workflows.Simulate domain-specific datasets (adverse events, labs, demographics, drug exposure) with variability and referential integrity.Develop connectors for Define-XML, Pinnacle21 validation, and statistical programming workflows.???? AI/ML in Data GenerationApply generative AI (LLMs, GANs, diffusion models) to model realistic clinical scenarios.Create synthetic patient journeys across EDC, e COA, CTMS, LIMS, and PV systems.Use AI-driven automation to simulate rare or complex cases for stress and edge-case testing.???? Compliance & Data GovernanceEnsure adherence to Gx P, 21 CFR Part 11, HIPAA, and GDPR standards.Implement anonymization/obfuscation while maintaining clinical and statistical fidelity.Produce validation protocols and documentation for audit and inspection readiness.???? Collaboration & IntegrationWork with Clinical Data Management, Biostatistics, Pharmacovigilance, and Compliance teams to gather requirements.Embed test data generation into CI/CD pipelines, trial simulations, and automated validation environments.Partner with SMEs to validate AI-generated datasets for regulatory acceptability.Required Skills & QualificationsStrong Python expertise (pandas, Num Py, scikit-learn, Py Torch/Tensor Flow, Lang Chain, etc.).Hands-on experience generating synthetic clinical data or applying CDISC standards (SDTM, ADa M, Define-XML).Familiarity with clinical data management systems (Medidata Rave, Veeva CDB, Oracle In Form, etc.).Knowledge of Gx P/21 CFR Part 11 and regulated data handling.Experience with test automation frameworks (Py Test, Robot Framework) and validation tools (Pinnacle21).Preferred QualificationsBackground supporting clinical trial systems (EDC, CTMS, PV, LIMS, e COA).Understanding of statistical workflows (SAS, R) and integration into test pipelines.Cloud experience (AWS, Azure, GCP) for secure AI/ML deployment.Experience with inspection readiness and validation documentation in pharma.

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