
AI Driven Synthetic Data Engineer
2 weeks ago
Job Overview
This role involves designing and developing Python frameworks to generate synthetic clinical and operational datasets. The ideal candidate will have hands-on experience generating synthetic clinical data, applying CDISC standards (SDTM, ADaM), and working with clinical data management systems.
Key Responsibilities
- Build Python frameworks to create realistic synthetic datasets for various applications, including clinical trials and research studies.
- Ensure compliance with regulatory requirements, such as GxP, 21 CFR Part 11, HIPAA, and GDPR, by implementing robust data governance and validation processes.
- Develop AI-driven automation tools to simulate complex scenarios and edge cases, reducing the risk of errors and ensuring high-quality results.
- Collaborate closely with cross-functional teams, including Clinical Data Management, Biostatistics, Pharmacovigilance, and Compliance, to deliver effective solutions.
Required Skills & Qualifications
- Strong Python expertise with a focus on data science libraries (e.g., pandas, NumPy, scikit-learn) and deep learning frameworks (e.g., PyTorch, TensorFlow).
- Hands-on experience generating synthetic clinical data or applying CDISC standards (SDTM, ADaM, Define-XML).
- Familiarity with clinical data management systems (e.g., Medidata Rave, Veeva CDB, Oracle InForm).
- Knowledge of GxP/21 CFR Part 11 and regulated data handling practices.
- Experience with test automation frameworks (e.g., PyTest, Robot Framework) and validation tools (e.g., Pinnacle21).
Benefits
This role offers opportunities for professional growth and development in a collaborative environment, with access to cutting-edge technologies and methodologies.
What We Offer
We provide competitive compensation packages, comprehensive benefits, and a dynamic work environment that encourages innovation and creativity.
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