Data Scientist

The role of the Data Scientist in RAG & Document Intelligence focuses on designing and implementing AI solutions that enhance the accessibility of knowledge within an organization, transforming complex enterprise documents into actionable insights.

• Strong Python skills with experience in machine learning and generative AI workflows.
• Solid understanding of NLP principles like text representation and semantic search.
• Experience in designing and optimizing RAG pipelines for unstructured documents.
• Proficiency with document parsing and handling diverse formats.
• Familiarity with evaluation frameworks for LLMs and defining specific quality metrics.
• Knowledge of multi-agent AI frameworks.
• Experience with vector databases and cloud services (Azure/AWS).
• Strong analytical skills with an experimental approach to problem solving.
• Fluent in English (written and spoken).

Nice to have:

• Hands-on experience with Databricks GenAI products.
• API development and integration skills.
• Familiarity with Model Context Protocol.
• Knowledge of knowledge management and taxonomy design.

• Optimize RAG pipelines by experimenting with various strategies for parsing, chunking, and retrieval to improve answer quality and reduce errors.
• Extract structured information from unstructured content, ensuring high-quality input for processing.
• Design and conduct experiments to evaluate models based on accuracy, latency, and cost, and derive insights from the data.
• Implement NLP techniques to solve real-world problems, enhancing user experience through effective query handling.
• Monitor and evaluate the performance of AI models and make necessary adjustments for cost-efficiency.