At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. In data engineering at PwC, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis. You will be responsible for developing and implementing data pipelines, data integration, and data transformation solutions.
Years of Experience: 11
+ year of experiencePricewaterhouseCoopers Acceleration Center (PwC AC) is the natural extension of PwC's leading-class global delivery capabilities. Our highly skilled resources assist with software development, ERP programming development, application integration and support and maintenance services. Bangalore AC provides premium, cost-effective, high-quality technology services for projects based in the United States and global clients focused on key horizontal and vertical end-to-end solutions.
Roles And Responsibilities
At PwC - AC, as a AI Solution QA is responsible for leading quality assurance practices for AI solutions, ensuring that they meet stringent quality standards and deliver superior value to our clients. This role will involve developing QA frameworks, implementing best practices, managing QA teams, and overseeing comprehensive testing strategies.
Mandatory Skills
- Define, implement, and manage AI-specific QA standards and methodologies.
- Lead a team of QA professionals to ensure rigorous testing of AI applications, models, and integrations.
- Develop comprehensive testing frameworks for AI and Machine Learning models, including performance, accuracy, explainability, fairness, bias, and security.
- Collaborate with AI architects, developers, data scientists, and stakeholders to integrate QA practices into the development lifecycle.
- Manage risk assessment processes, proactively identifying potential quality and reliability issues.
- Conduct and oversee testing activities including regression, integration, system, and user acceptance testing.
- Provide strategic oversight to ensure compliance with internal standards and external regulatory requirements related to AI.
- Mentor QA team members, facilitating professional growth and technical capability enhancement.
Preferred Knowledge
- Minimum 10-12 years of experience in software QA/testing with at least 3-5 years specifically in AI/ML quality assurance.
- Proven track record managing QA teams, implementing robust QA practices, and driving quality improvements.
- Strong understanding of AI/ML concepts, model evaluation, testing techniques, and AI-specific quality metrics.
- Familiarity with AI regulatory standards and ethical considerations.
- Experience with AI and ML tools such as TensorFlow, PyTorch, AWS SageMaker, Azure ML, or similar platforms.
- Excellent communication, stakeholder management, and problem-solving skills.
Educational Qualifications:
BE / B Tech / MCA / M Tech
Certifications:
Certified Software Quality Analyst (CSQA), AWS Certified Machine Learning Specialty, Azure AI Engineer Associate, Google Professional Machine Learning Engineer
Preferred Skills
- Good analytical & problem-solving skills.
- Good communication and presentation skills.
