Embedded Data Scientist, Chanakya

Understand the client's data landscape across documents, imagery, audio, geospatial data, and structured records — including data sources, formats, workflows, and domain terminology.

Design domain ontologies representing entities, relationships, hierarchies, and operational concepts within the client's data environment.

Define document segmentation and chunking strategies that preserve semantic meaning and support effective retrieval.

Work with heterogeneous datasets and define how different modalities should be indexed, embedded, and linked.

Strong Python skills including pandas, NumPy, and modern NLP or LLM tooling.

Solid grounding in ML fundamentals — enough to understand model behaviour, contribute to evaluation design…

Experience working with large unstructured datasets including documents, transcripts, reports, or operational records.

Familiarity with LLM-based systems, retrieval pipelines, or vector search systems.