Generative AI- Data Scientist-Senior Associate

At PwC, our people in data and analytics focus on leveraging data to drive insights and make informed business decisions. They utilise advanced analytics techniques to help clients optimise their operations and achieve their strategic goals. In data analysis at PwC, you will focus on utilising advanced analytical techniques to extract insights from large datasets and drive data-driven decision-making. You will leverage skills in data manipulation, visualisation, and statistical modelling to support clients in solving 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 team you will develop and implement innovative machine learning models for GenAI projects. As a Senior Associate, you will analyze complex problems, mentor junior team members, and build meaningful client relationships while navigating the evolving landscape of data science. Join us to leverage your technical knowledge and contribute to groundbreaking solutions that shape the future of AI.

Responsibilities

• Develop and implement agentic AI systems — including tool-calling, autonomous task planning and execution, multi-step reasoning workflows, agent memory management, and human-in-the-loop escalation mechanisms for complex enterprise use cases. Leverage Agentic frameworks like LangGraph, CrewAI, Autogen, cloud-based frameworks, etc.
• Develop and deploy agentic AI solutions using any of the cloud-native services as per defined requirement (Azure AI Foundry, AWS Bedrock Agents, GCP Vertex AI Agent Builder, etc.), and associated cloud services for scalable agent execution.
• Implement and maintain evaluation frameworks for agentic AI solutions — assessing agent reasoning, tool-use reliability, multi-step task completion, hallucination risk, and autonomous decision quality to ensure production readiness and continuous performance improvement.
• Design, develop, and optimize RAG pipelines end-to-end (using LangChain, LlamaIndex, etc.) — including chunking strategies, embedding model selection, integrate production-grade vector databases (Pinecone, Weaviate, OpenSearch, Azure AI Search, etc.), hybrid retrieval, re-ranking.
• Design, develop, and optimize prompt engineering strategies, including prompt chaining, few-shot/zero-shot techniques, and prompt templating, to enhance the accuracy, reliability, and consistency of LLM-powered applications and agentic workflows.
• Collaborate with cross-functional teams (client managers, data scientists, architects, DevOps engineers) to translate business requirements into technical implementations — ensuring alignment with solution architecture defined by the lead architects.
• Implement and uphold Python development best practices during implementation.
• Monitor solution performance, track key metrics, test all affected scenarios and proactively adjust implementations — identifying issues in accuracy, latency, throughput, and cost, and applying optimizations at the code and infrastructure level.
• Communicate technical findings, implementation progress, and insights to stakeholders — contributing to documentation, sprint demos, and knowledge-sharing within the team

What You Must Have

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

What Sets You Apart

• Proven experience building and deploying production-grade Agentic AI solutions using frameworks like LangChain, LangGraph, CrewAI, or AutoGen.
• Strong knowledge of AI interoperability protocols (e.g., MCP, A2A) and advanced Retrieval
• Augmented Generation (RAG) architectures such as Graph RAG, Vectorless RAG, and Hybrid RAG.
• Deep understanding of traditional AI/ML fundamentals including model building, fine-tuning, quantization, feature engineering, and model evaluation.
• Foundational awareness of Responsible AI principles, security practices for safe deployments, and experience evaluating GenAI and Agentic AI applications.
• Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP), familiarity with CI/CD pipelines, and relevant AI/GenAI certifications preferred.