Senior Ai Architect For Synthetic Data Generation

2 weeks ago

Gandhinagar, Gujarat, India beBeeArtificialIntelligence Full time US$ 1,55,000 - US$ 1,85,000
Job Description

We are seeking a highly skilled 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
    • Create 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 and Qualifications
    • Strong Python Expertise
      • Pandas, NumPy, scikit-learn, PyTorch/TensorFlow, LangChain, etc.
    • Clinical Data Generation
      • Hands-on experience generating synthetic clinical data or applying CDISC standards (SDTM, ADaM, Define-XML).
    • Clinical Data Systems
      • Familiarity with clinical data management systems (Medidata Rave, Veeva CDB, Oracle InForm, etc.).
    • Gxp Standards
      • Knowledge of GxP/21 CFR Part 11 and regulated data handling.
    • Test Automation Frameworks
      • Experience with test automation frameworks (PyTest, Robot Framework) and validation tools (Pinnacle21).
      Preferred Qualifications
      • Clinical Trial Support
        • Background supporting clinical trial systems (edc, ctms, pv, lims, ecoa).
      • Statistical Workflows
        • Understanding of statistical workflows (SAS, R) and integration into test pipelines.
      • Cloud Experience
        • Cloud experience (aws, azure, gcp) for secure Ai/ml deployment.
      • Inspection Readiness
        • Experience with inspection readiness and validation documentation in pharma.

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