N Human Resources & Management Systems

Data Scientist – Advanced Analytics

Posted 4 Days Ago

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Bengaluru North, Yelahanka, Bengaluru Urban, Karnataka, IND

In-Office

13-15 Annually

Senior level

HR Tech • Professional Services • Consulting

The Role

Design, build, and optimize Retrieval-Augmented Generation systems for large-scale document understanding and advanced analytics. Responsibilities include developing retrieval and chunking strategies, improving indexing accuracy and context relevance, fine-tuning models, engineering prompts, managing token limits and latency, integrating LLM frameworks and APIs, evaluating output quality, and collaborating on scalable deployment. The role requires strong Python, RAG, vector database, embedding, LLM tooling, and inference optimization expertise.

Summary Generated by Built In

Data Scientist – Advanced Analytics

Experience Required: 6+ years total (2+ years relevant in RAG / LLM-based systems)

Location: Open / Any Location (India)

Compensation: ₹13 – ₹15 LPA

Employment Type: Full-time

Role Overview:

We are looking for an experienced Data Scientist – Advanced Analytics with strong expertise in Python, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG) systems. The ideal candidate will be responsible for designing, building, and optimizing intelligent retrieval systems that combine LLM reasoning with real-time document understanding

Key Responsibilities:

Design and implement Retrieval-Augmented Generation (RAG) pipelines and architectures.
Develop document retrieval, contextual augmentation, and chunking strategies for large-scale unstructured data.
Optimize RAG indexing, retrieval accuracy, and context relevance using advanced evaluation metrics.
Implement fine-tuning and prompt engineering techniques to improve retrieval and generation quality.
Manage token limits, context windows, and retrieval latency for high-performance inference.
Integrate LLM frameworks like LangChain or LlamaIndex for pipeline orchestration.
Utilize APIs from OpenAI, Hugging Face Transformers, or other LLM providers for model integration.
Perform noise reduction, diversity sampling, and retrieval optimization to enhance output reliability.
Collaborate with cross-functional teams to deploy scalable RAG-based analytics solutions.

Requirements

Programming: Strong hands-on experience with Python.

✅ RAG Expertise: In-depth understanding of RAG pipelines, RAG architecture, and retrieval optimization.

✅ Vector Databases: Practical experience with FAISS, Pinecone, Weaviate, ChromaDB, or Milvus.

✅ Embedding Models: Knowledge of generating and fine-tuning embeddings for semantic search and document retrieval.

✅ LLM Tools: Experience with LangChain, LlamaIndex, OpenAI API, and Hugging Face Transformers.

✅ Optimization: Strong understanding of token/context management, retrieval latency, and inference efficiency.

✅ Evaluation Metrics: Familiarity with Retrieval Accuracy, Context Relevance, and Answer Faithfulness.

Good to Have:

Experience in MLOps for deploying and monitoring LLM/RAG-based solutions.
Understanding of semantic search algorithms and context ranking models.
Exposure to knowledge retrieval, contextual augmentation, or multi-document summarization.
Master’s degree in Computer Science, Artificial Intelligence, Data Science, or related field.

Skills Required

6+ years of total professional experience
2+ years of relevant experience building RAG or LLM-based systems
Strong hands-on experience with Python
In-depth understanding of RAG pipelines, RAG architecture, and retrieval optimization
Practical experience with vector databases such as FAISS, Pinecone, Weaviate, ChromaDB, or Milvus
Knowledge of generating and fine-tuning embeddings for semantic search and document retrieval
Experience with LangChain, LlamaIndex, OpenAI API, and Hugging Face Transformers
Strong understanding of token and context management, retrieval latency, and inference efficiency
Familiarity with retrieval accuracy, context relevance, and answer faithfulness metrics
Experience in MLOps for deploying and monitoring LLM/RAG-based solutions
Understanding of semantic search algorithms and context ranking models
Exposure to knowledge retrieval, contextual augmentation, or multi-document summarization
Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field

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The Company

Year Founded: 2009

What We Do

nHRMS is a strategic human-resources partner providing end-to-end solutions for organizations in the United States and India. Its services span executive search and talent acquisition, performance management, HR advisory, organization strategy, HR technology, leadership development, labor-code compliance, workforce productivity, and learning. The firm supports clients across the employee lifecycle, combining people-first consulting with technology-enabled systems to help organizations scale.