NTT DATA seeks a Senior QA/QC Data Analyst specializing in AI/ML testing to join our dynamic team in Bangalore. This role is pivotal for ensuring the integrity and performance of our data and AI models. We are looking for innovative individuals passionate about growing with us in an inclusive and forward-thinking organization.

This position offers the opportunity to work on cutting-edge AI/ML technologies, contributing significantly to project success and client satisfaction. Your expertise will be crucial in evaluating data quality and validating AI model outcomes against stringent criteria.

- Oversee project responsibilities and operate autonomously within a collaborative setting. - Conduct comprehensive data evaluations for accuracy, completeness, consistency, validity, timeliness, uniqueness, and integrity. - Define and enforce quality benchmarks for data accuracy, completeness, validity, and AI model performance. - Test data ingestion, transformation (ETL/ELT), and output processes to ensure end-to-end integrity. - Certify that AI/ML datasets are accurate, representative, unbiased, and fit for purpose. - Validate model performance metrics against business and technical benchmarks, including precision, recall, and stability. - Identify and assess bias, fairness concerns, and unintended consequences in data and AI model outputs. - Develop and implement automated tests for data validation, model regression, and pipeline checks within CI/CD and MLOps frameworks. - Log, prioritize, and track data and AI defects, performing root cause analysis and implementing corrective actions. - Ensure compliance with data governance, privacy, security, and AI regulatory standards. - Monitor for data drift, model drift, anomalies, and performance degradation post-deployment. - Communicate quality status, risks, and recommendations effectively to stakeholders. - Design and create testing plans, test cases, and scripts for thorough data evaluation. - Document and report defects, inconsistencies, and inaccuracies. - Maintain testing documentation and report on outcomes, documenting key data processes.

- Ability to assume project ownership and work independently within a team structure. - Strong analytical skills for problem-solving, root cause analysis, and solution development. - Proficiency in PyTest/unit test frameworks for ML testing and automation. - Expertise in automated test suite development for ML models and ML-specific API testing (e.g., inference endpoints). - Working knowledge of automated metrics validation for model outputs and ML-specific QA strategy (model tests, feature tests, data contracts, drift tests). - Proficiency in CI/CD integration for ML (MLOps) and model-centric regression testing. - Experience with testing lineage, reproducibility, and experiment tracking. - Skilled in developing and maintaining comprehensive test plans, scenarios, cases, defect tracking, reporting, and scripts. - Familiarity with ETL tools for data movement and transformation. - Understanding of AI governance frameworks, ethical AI, compliance, bias monitoring, and model traceability. - Proficiency with version control using Git (branching, collaboration, pull requests, merge conflicts). - Knowledge of build servers (e.g., Azure CICD Pipeline, Jenkins) and source control systems (e.g., DevOps, GitHub). - Experience with release management and bug tracking tools. - Familiarity with API testing using Postman and Swagger UI. - A bachelor’s degree in a related field or equivalent practical experience is required, with a minimum of 5 years of relevant work experience. - An ISTQB or equivalent certification is preferred.