Validation/QA Specialist – Supporting GT&E Data Scientists

Job Title: Validation/QA Specialist – Supporting GT&E Data Scientists Location: Bangalore / Mangalore Type: Full-Time Exp- 6-10Years CTC- up to 30lpa About the Role We are seeking a skilled Validation/QA Specialist to support a team of data scientists working on machine learning and AI-driven solutions. The ideal candidate will serve as the SME for model qualification, validation, documentation, and quality assurance activities. This role involves collaborating with cross-functional teams, ensuring technical accuracy, and maintaining compliance with documentation and validation processes. It offers an opportunity to work on impactful data science initiatives in a dynamic and collaborative environment. Roles and Responsibilities Act as the QA/Validation SME for machine learning models developed by the data science team. Create and maintain Qualification Plans and Technical Specification documents in partnership with data scientists and project teams. Document business and technical requirements for ML models, including accuracy, performance, compliance, and functionality. Collaborate with subject matter experts to evaluate, test, and validate ML models. Review and approve test cases to ensure alignment with model requirements and performance criteria. Generate validation summary reports in accordance with qualification documentation. Analyze and interpret test results; provide detailed feedback to enhance model performance. Ensure all documentation complies with validation standards, guidelines, and best practices. Key Skills & Qualifications Basic understanding of statistical analysis concepts. Experience or familiarity with Computer System Validation (CSV) or Quality Assurance processes within digital/IT environments. Working knowledge of programming languages such as Python, R, Java, and/or C++. Understanding of the AI/ML lifecycle, data science workflows, and software development processes. Experience with AI/ML modeling—preferably in healthcare, life sciences, pharmaceutical, or related data environments. Background in pharmaceutical manufacturing processes or chemical engineering is highly preferred. Strong documentation, analytical, and communication skills. Ability to collaborate effectively with data scientists, SMEs, and project stakeholders.