Python AI Engineer – Synthetic Test Data

21 hours ago

India Saxon Global Full time

Python AI Engineer – Synthetic Test Data (Life Sciences / GxP)

About the Role

We 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 GxP-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 Automation

  • Build Python frameworks to generate synthetic clinical and operational datasets.
  • Produce CDISC-compliant datasets (SDTM, ADaM) 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 Generation

  • Apply generative AI (LLMs, GANs, diffusion models) to model realistic clinical scenarios.
  • 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 & Data Governance

  • Ensure adherence to GxP, 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 & Integration

  • Work 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 & Qualifications

  • Strong Python expertise (pandas, NumPy, scikit-learn, PyTorch/TensorFlow, LangChain, 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).

Preferred Qualifications

  • Background supporting clinical trial systems (EDC, CTMS, PV, LIMS, eCOA).
  • 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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