National Delivery Excellence- QA AI Performance Tester- Senior Associate

Overview

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. Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven decision making. You will work on developing predictive models, conducting statistical analysis, and creating data visualisations to solve complex business problems.

Focused on relationships, you are building meaningful client connections, and learning how to manage and inspire others. Navigating increasingly complex situations, you are growing your personal brand, deepening technical expertise and awareness of your strengths. You are expected to anticipate the needs of your teams and clients, and to deliver quality. Embracing increased ambiguity, you are comfortable when the path forward isn’t clear, you ask questions, and you use these moments as opportunities to grow.

Skills

Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to:

• Respond effectively to the diverse perspectives, needs, and feelings of others.
• Use a broad range of tools, methodologies and techniques to generate new ideas and solve problems.
• Use critical thinking to break down complex concepts.
• Understand the broader objectives of your project or role and how your work fits into the overall strategy.
• Develop a deeper understanding of the business context and how it is changing.
• Use reflection to develop self awareness, enhance strengths and address development areas.
• Interpret data to inform insights and recommendations.
• Uphold and reinforce professional and technical standards (e.g. refer to specific PwC tax and audit guidance), the Firm's code of conduct, and independence requirements.
  
  

The Opportunity

When you join PwC Acceleration Centers (ACs), you step into a pivotal role focused on actively supporting various Acceleration Center services, from Advisory to Assurance, Tax and Business Services. In our innovative hubs, you’ll engage in challenging projects and provide distinctive services to support client engagements through enhanced quality and innovation. You’ll also participate in dynamic and digitally enabled training that is designed to grow your technical and professional skills.

As part of the Data and Analytics Engineering team you will evaluate and enhance the performance of AI and Machine Learning systems. As a Senior Associate, you will bridge quality engineering and data science, guiding junior team members while maintaining that AI models perform effectively under real-world conditions, contributing to the continuous improvement of our testing frameworks.

Responsibilities

• Evaluate and enhance the performance of AI and Machine Learning systems
• Bridge quality engineering and data science to promote model performance
• Guide junior team members in practices for AI testing
• Contribute to the continuous improvement of testing frameworks
• Analyze data to identify areas for performance optimization
• Collaborate with engineering teams to implement solutions
• Stay informed on advancements in AI technologies
• Document processes and findings to support knowledge sharing
  
  

What You Must Have

• Bachelor's Degree
• 3 years of experience
• Oral and written proficiency in English required
  
  

What Sets You Apart

• Bachelor's or Master's Degree in Computer Science, Engineering
• Over 4 years of experience in performance testing
• 3 - 4 years of experience in AI/ML application testing
• Skilled in performance testing tools like JMeter and Locust
• Experienced in scripting languages such as Python or JavaScript
• Familiar with AI frameworks and model serving technologies
• Knowledgeable in MLOps, CI/CD, and cloud platforms
• Skilled in monitoring tools like Grafana and Datadog
• Familiarity with AI ethics and fairness testing