Synthetic Data Generation Specialist

6 days ago

Tirupati, Andhra Pradesh, India beBeeArtificialIntelligenceEngineer Full time ₹ 18,00,000 - ₹ 21,00,000

Transforming Clinical Trials with AI and Automation

Job Description

Synthetic test data plays a vital role in clinical trials, regulatory submissions, and GxP-compliant systems. As an AI Engineer – Synthetic Test Data, you will design and implement intelligent frameworks for synthetic and automated test data generation.

This role involves delivering 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:
  • 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).
Benefits
  • Contribute to the development of innovative AI solutions for clinical trials.
  • Collaborate with a team of experts in AI, statistics, and clinical research.
  • Work on projects that have a direct impact on public health and patient outcomes.
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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