Senior QA/QC Data Analyst with AI/ML testing

NTT DATA North America; Bengaluru Urban; Hybrid; INR 1,500,000 - 2,800,000; Full time

Job summary

NTT DATA North America is seeking a Senior QA/QC Data Analyst with AI/ML testing to join our Bangalore team. You will own data quality across ingestion, transformation, and model outputs, ensuring accuracy and bias mitigation while validating model metrics against business thresholds.

The role requires strong experience with PyTest, Python, ML testing, and CI/CD pipelines. Collaboration with data governance and AI governance teams is essential for compliant data processing and testing.

Qualifications

• Bachelor's degree in a computer science, information technology, or related field.
• Minimum 5 years of related work experience in QA/QC and data analytics for AI/ML.

Responsibilities

• Take ownership of data QA across AI/ML projects in Bangalore, ensuring data accuracy and integrity.
• Evaluate data quality across accuracy, completeness, consistency, validity, timeliness, and bias.
• Establish quality criteria for data and AI model performance; validate metrics against thresholds.
• Implement automated tests for data validation, model regression, and pipeline checks within CI/CD and MLOps workflows.
• Log, prioritize, and track defects; perform root cause analysis and corrective actions.
• Validate adherence to data governance, privacy, security, and AI regulatory requirements.

Skills

PyTest

Python

ML testing

CI/CD

MLOps

Data QA

Great Expectations

Education

Bachelor's degree in Computer Science

Tools

Azure CI/CD

Jenkins

CruiseControl

Git

Postman

Swagger UI

Fiddler

SQL

Job description

Req ID: 381528

NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization,

We are currently seeking a Senior QA/QC Data Analyst with AI/ML testing to join our team in Bangalore, Karnātaka (IN-KA), India (IN).

The following are the key responsibilities for this position:

• Take responsibility for the project and work independently in a collaborative environment.
• Evaluate data across various dimensions, including accuracy, completeness, consistency, validity, timeliness, uniqueness, and integrity.
• Establish quality criteria for data accuracy, completeness, consistency, validity, and AI model performance.
• Test data ingestion, transformation (ETL/ELT), and outputs to ensure source-to-target integrity.
• Verify that datasets used for AI/ML are accurate, representative, unbiased, and fit for purpose.
• Validate model metrics against defined business and technical thresholds, including accuracy, precision, recall, and stability.
• Identify and assess bias, fairness issues, and unintended impacts in data and AI model outcomes.
• Implement automated tests for data validation, model regression, and pipeline checks within CI/CD and MLOps workflows.
• Log, prioritize, and track data and AI defects; perform root cause analysis and corrective actions.
• Validate adherence to data governance, privacy, security, and AI regulatory requirements.
• Track data drift, model drift, anomalies, and performance degradation post-deployment.
• Communicate quality status, risks, and recommendations clearly to stakeholders before and after releases.
• Design and develop testing plans, test cases, and test scripts to evaluate data quality.
• Identify, document, and report defects, inconsistencies, and inaccuracies.
• Maintain and update testing documentation and report on test outcomes. Document key data processes and transformations.
• Assist with quality improvement initiatives and recommend improvements to data quality processes and procedures.
• Assist developers, business stakeholders, and data governance teams in meeting data quality standards.
• Knowledge of the Agile/Waterfall approach and how quality assurance fits into it.
• Create automated testing solutions from scratch.
• Develop testing scenarios by analyzing feature requirements for the purpose of estimating testing effort. Track defects, analyze and communicate test results, and engage in daily QA activities. Skills and Abilities:
• Ability to take ownership of the project and work independently in a team environment.
• Ability to analyze problems, perform root cause analysis, and develop solutions is essential for resolving data issues.
• Proficient in PyTest/unit test frameworks used for ML testing & automation
• Knowledge of programming languages such as C#, Python, or R for data process automation and analysis.
• Proficient in automated test suite development for ML models
• Working knowledge of ML-specific API testing (e.g., inference endpoints)
• Working knowledge of automated metrics validation for model outputs
• Expertise in the principles and testing procedures.
• Working knowledge of data validation frameworks such as Great Expectations
• Working knowledge of ML-oriented data pipeline tools .
• Working knowledge of validation for massive, ML-ready datasets
• Proficient in ML-specific QA strategy (model tests, feature tests, data contracts, drift tests).
• Working knowledge of CI/CD integration for ML (MLOps).
• Proficient in model-centric regression testing.
• Proficient in testing lineage, reproducibility, and experiment tracking.
• Proficient in developing and maintaining test plans, test scenarios, test cases, test defect tracking, summary reporting, and test scripts to perform thorough testing and validate the data, based on business requirements.
• Familiarity with Extract, Transform, Load (ETL) tools to move and transform data.
• Working knowledge of AI governance framework, ethical AI & compliance, bias monitoring policies, and model traceability requirements
• Working knowledge of debugging tools (Fiddler).
• Proficiency with version control practices using Git, including branching, collaboration, reviewing pull requests, and resolving merge conflicts.
• Knowledge of build servers. (Azure CICD Pipeline, Jenkins, and Cruise Control).
• Working knowledge of source control systems (DevOps, GitHub, SVN, or TFS).
• Working experience in release management and bug tracking tools (e.g., Zephyr, etc.).
• Knowledge of HTML5, CSS, JavaScript, Angular Bootstrap, SQL, SharePoint, JSON, or XML objects.
• Knowledge of API testing using Postman and Swagger UI.
• Knowledge of Azure cloud infrastructure and its capabilities.
• Strong verbal and written communication skills are needed to explain findings to both technical and non-technical stakeholders.
• A willingness to learn new tools and adapt to evolving technologies is important for long-term career growth. Minimum Qualifications:
• Bachelor’s degree in computer science, information systems, information technology, software engineering, computer engineering, or a related discipline.
• 5 years of related work experience.
• Equivalent additional directly related experience will be considered in lieu of a college degree. Preferred Qualification:
• ISTQB or equivalent certification preferred

About NTT DATA

NTT DATA is a $30 billion business and technology services leader, serving 75% of the Fortune Global 100. We are committed to accelerating client success and positively impacting society through responsible innovation. We are one of the world's leading AI and digital infrastructure providers, with unmatched capabilities in enterprise-scale AI, cloud, security, connectivity, data centers and application services. our consulting and Industry solutions help organizations and society move confidently and sustainably into the digital future. As a Global Top Employer, we have experts in more than 50 countries. We also offer clients access to a robust ecosystem of innovation centers as well as established and start‑up partners. NTT DATA is a part of NTT Group, which invests over $3 billion each year in R&D.

Whenever possible, we hire locally to NTT DATA offices or client sites. This ensures we can provide timely and effective support tailored to each client’s needs. While many positions offer remote or hybrid work options, these arrangements are subject to change based on client requirements. For employees near an NTT DATA office or client site, in‑office attendance may be required for meetings or events, depending on business needs. At NTT DATA, we are committed to staying flexible and meeting the evolving needs of both our clients and employees.

NTT DATA is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status. For our EEO Policy Statement, please click here. If you'd like more information on your EEO rights under the law, please click here. For Pay Transparency information, please click here.