AI & GenAI Data Scientist-Senior Associate Save for Later Remove job
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.
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.
Minimum Degree Required
Bachelor's Degree
Minimum Year(s) of Experience
4 year(s)
Demonstrates thorough-level abilities and/or a proven record of success managing the identification and addressing of client needs:
Building of GenAI and AI solutions, including but not limited to analytical model development and implementation, prompt engineering, general all-purpose programming (e.g., Python), testing, communication of results, front end and back-end integration, and iterative development with clients
Documenting and analyzing business processes for AI and Generative AI opportunities, including gathering of requirements, creation of initial hypotheses, and development of GenAI and AI solution approach
Collaborating with client team to understand their business problem and select the appropriate analytical models and approaches for AI and GenAI use cases
Designing and solutioning AI/GenAI architectures for clients, specifically for plugin-based solutions (i.e., ChatClient application with plugins) and custom AI/GenAI application builds
Processing unstructured and structured data to be consumed as context for LLMs, including but not limited to embedding of large text corpus, generative development of SQL queries, building connectors to structured databases
Support management of daily operations of a global data and analytics team on client engagements, review developed models, provide feedback and assist in analysis;
Directing data engineers and other data scientists to deliver efficient solutions to meet client requirements;
Leading and contributing to development of proof of concepts, pilots, and production use cases for clients while working in cross-functional teams;
Structuring, write, communicate and facilitate client presentations; and,
Directing associates through coaching, providing feedback, and guiding work performance.
Demonstrates thorough abilities and/or a proven record of success learning and performing in functional and technical capacities, including the following areas:
Managing AI/GenAI application development teams including back-end and front-end integrations
Using Python (e.g., Pandas, NLTK, Scikit-learn, Keras etc.), common LLM development frameworks (e.g., Langchain, Semantic Kernel), Relational storage (SQL), Non-relational storage (NoSQL);
Experience in analytical techniques such as Machine Learning, Deep Learning and Optimization
Vectorization and embedding, prompt engineering, RAG (retrieval, augmented, generation) workflow dev
Understanding or hands on experience with Azure, AWS, and / or Google Cloud platforms
Experience with Git Version Control, Unit/Integration/End-to-End Testing, CI/CD, release management, etc.
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