Job Description

Line of Service

Advisory

Industry/Sector

Not Applicable

Specialism

Data, Analytics & AI

Management Level

Senior Associate

& Summary

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 artificial intelligence and machine learning at PwC will focus on developing and implementing advanced AI and ML solutions to drive innovation and enhance business processes. Your work will involve designing and optimising algorithms, models, and systems to enable intelligent decision-making and automation.

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.

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.

Responsibilities

· Lead the design, development, and deployment of production-level machine learning models, with a focus on generative AI models such as Large Language Models (LLMs), Generative Adversarial Networks (GANs), and Variational Autoencoders (VAEs).

· Provide advanced technical support for existing AI models, including bug fixes, addressing complex issues, andfacilitatingmodel expansion for new business cases.

· Act as a liaison between data scientists, cloud engineers, data engineers, and the business team to diagnose and resolve issues related to model performance and deployment.

· Lead the continuous improvement of support processes and workflows for ML applications.

· Develop,monitor, andmaintainend-to-end machine learning pipelines (MLOps) including data preparation, feature engineering, model training, and deployment.

·UtilizeAzure AI Foundry to build, test, and deploycutting-edgeAI-driven solutions and generative AI applications.

· Build model performance benchmarking, evaluation, and monitoring capabilities.

· Assess model performance to understand bugs, inefficiencies, and their root cause.

· Document and communicate best practices and troubleshooting procedures to support teams and stakeholders.

· Coordinate and mentor the Machine Learning Engineering team, promoting best practices and code quality.

· Stay current with the latest advancements in AI and machine learning technologies to provide informed support and recommendations.

Mandatory skill sets:

· Strong experience working with advanced data analysis on large datasets.

· Hands-on experience with Azure for managing the end-to-end ML lifecycle.

· Proven experience with Azure AI Foundry for building and deploying AI-driven solutions.

· Familiarity with Snowflake and its AI/ML offerings.

· Experience in both front-end(UI/UX) and backend (API development, database management) technologies to build end-to-end solutions.

·Proficiencywith data science and data engineering tools such as scikit-learn,XGBoost, pandas, NumPy, SciPy, andJupyternotebooks.

· Strong understanding of software engineering tools and practices (Python, Git, CI/CD principles).

Preferred skill sets

· Excellent problem-solving skills and attention to detail.

· Must be able to function independently as well as work in a collaborative team environment.

· Willingness to teach and learnnew technologies

Years of experiencerequired

4 – 7 yrs

Education qualification

Btech/MBA/MCA

Education (if blank, degree and/or field of study not specified)

Degrees/Field of Study required: Bachelor of Engineering, Master of Business AdministrationDegrees/Field of Study preferred:

Certifications (if blank, certifications not specified)

Required Skills

Artificial Intelligence (AI)

Optional Skills

Accepting Feedback, Accepting Feedback, Active Listening, AI Implementation, Analytical Thinking, C++ Programming Language, Communication, Complex Data Analysis, Creativity, Data Analysis, Data Infrastructure, Data Integration, Data Modeling, Data Pipeline, Data Quality, Deep Learning, Embracing Change, Emotional Regulation, Empathy, GPU Programming, Inclusion, Intellectual Curiosity, Java (Programming Language), Learning Agility, Machine Learning {+ 25 more}

Desired Languages (If blank, desired languages not specified)

Travel Requirements

Not Specified

Available for Work Visa Sponsorship?

No

Government Clearance Required?

No

Job Posting End Date

March 30, 2026