Synthetic Test Data Specialist

2 weeks ago

Bellary, Karnataka, India beBeeSynthetic Full time US$ 1,20,000 - US$ 1,80,000
AI Engineer for Synthetic Test Data Generation

We are seeking an experienced Python AI Engineer to design and implement intelligent frameworks for generating high-quality, audit-ready synthetic test data in support of clinical trials, regulatory submissions, and GxP-compliant systems.

This role will leverage AI/ML and Python automation to deliver datasets that reduce reliance on production data, accelerate testing cycles, and ensure compliance with FDA, EMA, and global regulatory standards.

Key Responsibilities
  • Build Intelligent Frameworks: Generate realistic clinical scenarios with variability and referential integrity using generative AI (LLMs, GANs, diffusion models).
  • Produce Compliant Datasets: Deliver SDTM, ADaM, and Define-XML compliant datasets for data transformation, analysis, and reporting workflows.
  • Develop Connectors: Integrate with Define-XML, Pinnacle21 validation, and statistical programming workflows.
Achievements in AI and ML
  • Apply Generative AI: Model complex clinical scenarios using LLMs, GANs, and diffusion models.
  • Create Realistic Patient Journeys: Simulate patient journeys across EDC, eCOA, CTMS, LIMS, and PV systems.
  • Use AI-Driven Automation: Simulate rare or complex cases for stress and edge-case testing.
Compliance and Governance
  • Ensure Compliance: Comply with GxP, 21 CFR Part 11, HIPAA, and GDPR standards.
  • Implement Anonymization: Maintain clinical and statistical fidelity while ensuring anonymization and obfuscation.
  • Document Validation Protocols: Document for audit and inspection readiness.
Required Skills and Qualifications
  • Python Expertise: Proficiency in pandas, NumPy, scikit-learn, PyTorch/TensorFlow, LangChain, etc.
  • Hands-On Experience: Generating synthetic clinical data or applying CDISC standards (SDTM, ADaM, Define-XML).
  • Clinical Data Management: Familiarity with Medidata Rave, Veeva CDB, Oracle InForm, etc.
  • GxP Knowledge: Regulated data handling.
  • Test Automation: Experience with PyTest, Robot Framework) and validation tools (Pinnacle21).
  • Background in Clinical Trial Systems: EDC, CTMS, PV, LIMS, eCOA.
  • Statistical Workflows: SAS, R integration into test pipelines.
  • Cloud Experience: Secure AI/ML deployment (AWS, Azure, GCP).
  • Inspection Readiness: Validation documentation in pharma.
Saxon Global is an equal opportunity employer. We welcome applicants from diverse backgrounds and perspectives.

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