Generative AI- Data Scientist- Associate 2

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.

Years of Experience: Candidates with 2+ years of hands on experience

PwC US - Acceleration Center is seeking a highly skilled and experienced GenAI Data Scientist to join our team at Associate level. As a GenAI Data Scientist, you will play a critical role in developing and implementing machine learning models and algorithms for our GenAI projects. The ideal candidate should have a strong background in data science, with a focus on GenAI technologies, and possess a solid understanding of statistical analysis, machine learning, data visualization, and application programming.

Responsibilities

• Collaborate with product, engineering, and domain experts to identify high-impact GenAI opportunities and create actionable road maps.
• Design, build, and iterate on GenAI and Agentic AI solutions end-to-end, encompassing agent architecture and orchestration, tool and memory integration, goal-directed planning and execution, analytical model development, prompt engineering, robust testing, CI/CD, and full-stack integration.
• Process structured and unstructured data for LLM workflows by applying vectorization and embedding, intelligent chunking, RAG pipelines, generative SQL creation and validation, scalable connectors for databases and APIs, and rigorous data-quality checks.
• Validate and evaluate models, RAGs and agents through quantitative and qualitative metrics, perform error analysis, and drive continuous performance tuning.
• Containerize and deploy production workloads on Kubernetes and leading cloud platforms (Azure, AWS, GCP).
• Communicate findings and insights via dashboards, visualizations, technical reports, and executive-level presentations.
• Stay current with GenAI advancements and champion innovative practices across the organization.
  
  

Requirements

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field.
• 1-2 years of hands-on experience delivering GenAI solutions, complemented by 3-5 years of deploying machine learning solutions in production environments.
• Strong proficiency in Python including object-oriented programming (OOP), with additional experience in R or Scala valued.
• Proven experience with vector stores and search technologies (e.g., FAISS, pgvector, Azure AI Search, AWS OpenSearch).
• Experience with LLM-backed agent frameworks including LangChain, LangGraph, AutoGen, and CrewAI, as well as RAG patterns.
• Expertise in data preprocessing, feature engineering, and statistical experimentation.
• Competence with cloud services across Azure, AWS, or Google Cloud, including Kubernetes and Docker.
• Solid grasp of Git workflows, automated testing (unit, integration, end-to-end), and CI/CD pipelines.
• Proficiency in data visualization and storytelling for both technical and non-technical audiences.
• Strong problem-solving skills, collaborative mindset, and ability to thrive in a fast-paced environment.
  
  

Nice To Have Skills

• Relevant certifications in GenAI tools and technologies.
• Hands-on experience with leading agent orchestration platforms such as Agentspace (Google), Agentforce (Salesforce), and Mosaic AI (Databricks).
• Proven experience in chatbot design and development, including conversational flow, intent recognition, and backend integration.
• Practical knowledge of ML/DL frameworks such as TensorFlow, PyTorch, and scikit-learn.
• Proficient in object-oriented programming with languages such as Java, C++, or C#.
  
  

Professional And Educational Background

• BE / B.Tech / MCA / M.Sc / M.E / M.Tech / MBA/ Any Degree