AI & GenAI Data Scientist-Senior Associate

$84,000 - $202,000/Yr

PricewaterhouseCoopers - New York, NY

Full-time - Mid Level

New York, NY

Professional, Scientific, and Technical Services

About the position

At PwC, the data and analytics team focuses on leveraging data to drive insights and make informed business decisions. The role involves utilizing advanced analytical techniques to extract insights from large datasets, supporting clients in solving complex business problems, and building meaningful client connections. The position emphasizes personal growth, technical expertise, and the ability to navigate ambiguity while delivering quality results.

Responsibilities

• Utilize advanced analytical techniques to extract insights from large datasets.
• Support clients in solving complex business problems through data-driven decision-making.
• Build meaningful client connections and manage relationships effectively.
• Anticipate the needs of teams and clients to deliver quality results.
• Document and analyze business processes for AI and Generative AI opportunities.
• Collaborate with client teams to understand business problems and select appropriate analytical models.
• Design and solution AI/GenAI architectures for clients, including plugin-based solutions.
• Process unstructured and structured data for context in LLMs.
• Support management of daily operations of a global data and analytics team on client engagements.
• Direct data engineers and data scientists to deliver efficient solutions.
• Lead development of proof of concepts, pilots, and production use cases for clients.
• Structure, write, communicate, and facilitate client presentations.
• Coach and provide feedback to associates to guide work performance.

Requirements

• Experience in managing AI/GenAI application development teams.
• Proficiency in Python and related libraries (e.g., Pandas, NLTK, Scikit-learn, Keras).
• Familiarity with common LLM development frameworks (e.g., Langchain, Semantic Kernel).
• Experience with relational (SQL) and non-relational (NoSQL) storage.
• Knowledge of analytical techniques such as Machine Learning, Deep Learning, and Optimization.
• Understanding of Azure, AWS, and/or Google Cloud platforms.
• Experience with Git Version Control and CI/CD processes.

Nice-to-haves

• Experience in prompt engineering and RAG (retrieval, augmented, generation) workflow development.
• Ability to use critical thinking to break down complex concepts.
• Experience in developing and implementing analytical models.

Benefits

• Medical insurance
• Dental insurance
• Vision insurance
• 401k plan
• Holiday pay
• Vacation pay
• Annual discretionary bonus