Zalak Karnik
@zalakkarnik
I build production RAG, machine learning, and financial risk systems.
What I'm looking for
At Casepoint, I architect and deploy RAG pipelines for semantic search, Text-to-SQL, and document summarization, reducing manual review time by approximately 50% across three production use cases. I also designed hybrid BM25, vector search, and reranking retrieval that reduced irrelevant outputs by 40%.
Previously at L&T Finance, I improved loan-disbursement prediction accuracy by 15%, reduced fraud-detection time by 30%, and managed 50M+ financial records in BigQuery. I build end-to-end AI products, from multi-agent financial research platforms to Gemini-powered PDF chatbots, using Python, cloud ML platforms, and reliable retrieval systems.
Experience
Work history, roles, and key accomplishments
Associate Data Scientist (Gen AI)
Casepoint
Dec 2024 - Present (1 year 8 months)
Architected and deployed RAG pipelines for semantic search, Text-to-SQL, and document summarization, reducing manual review time by ~50%. Engineered hybrid retrieval with BM25, vector search, and reranking, improving precision and reliability.
Education
Degrees, certifications, and relevant coursework
MIT World Peace University
Master of Science, Data Science and Big Data Analytics
2022 - 2024
Grade: CGPA 9.15/10
Pursued a Master of Science in Data Science and Big Data Analytics, achieving a CGPA of 9.15/10.
Tech stack
Software and tools used professionally
Availability
Location
Authorized to work in
Job categories
Skills
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