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Data Scientist


Required Skills/Experience:
  • Core Skills: Experience delivering AIML production systems, conversational AI, LLMs, GPT models.
  • Programming: Python and AIML libraries.
  • Cloud/Platforms: Azure AI, Snowflake.
  • Key Concept: Agent workflow - automating tasks by chaining AI agents (e.g., for recruitment sourcing).
  • Traditional ML: Ability to build, train, and deploy custom ML models.
  • Vector Database: Hands-on experience with vector databases for semantic search and efficient data retrieval in RAG implementations.
  • Snowflake Cortex: Strong experience in Snowflake, specifically Snowflake Cortex for building internal UIs and applications. 1-2 years hands-on experience in Snowflake is sufficient.
  • LLMs Used: Azure AI (GPT-4, GPT 4.2), exploring Gemini Pro. Traditional models include Llama-based models (e.g., 70 billion parameters).
  • Data Sources: Primarily Snowflake data lake, potentially Azure and AWS S3.
  • Financial Background: Good to have experience in financial or regulated industries, or an understanding of finance-related business questions.
  • Testing: Basic unit testing and generation of unit test cases are required.

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