LAKKAM SUPRAJA

Data Scientist

Hyderabad, India 1+ yrs exp 82 · Excellent

About

Data Scientist with 2+ years of experience specializing in Generative AI, Retrieval-Augmented Generation (RAG), and agentic systems. Proficient in architecting stateful multi-agent workflows using LangGraph and LangChain, optimizing semantic retrieval pipelines, and productionizing scalable LLM applications via FastAPI, Docker, and AWS. Proven track record of improving retrieval relevance, reducing latency, and automating enterprise knowledge operations via structured prompt engineering and deterministic tool calling.

Skills & Expertise (32)

NumPy Intermediate

7.0/10

Years Exp

Pandas Intermediate

7.0/10

Years Exp

RAG Intermediate

7.0/10

Years Exp

scikit-learn Intermediate

7.0/10

Years Exp

Prompt Engineering Intermediate

7.0/10

Years Exp

Embeddings Intermediate

7.0/10

Years Exp

TensorFlow Intermediate

7.0/10

Years Exp

LangChain Intermediate

7.0/10

Years Exp

LangGraph Intermediate

7.0/10

Years Exp

Hugging Face Intermediate

7.0/10

Years Exp

PyTorch Intermediate

7.0/10

Years Exp

Python Intermediate

6.6/10

Years Exp

SQL Intermediate

6.4/10

Years Exp

Postgresql Intermediate

6.4/10

Years Exp

Agentic Workflows Intermediate

6.0/10

Years Exp

MLflow Intermediate

6.0/10

Years Exp

REST APIs Intermediate

6.0/10

Years Exp

FastAPI Intermediate

6.0/10

Years Exp

Docker Intermediate

6.0/10

Years Exp

AWS Glue Intermediate

6.0/10

Years Exp

AWS EC2 Intermediate

6.0/10

Years Exp

AWS S3 Intermediate

6.0/10

Years Exp

AWS SageMaker Intermediate

6.0/10

Years Exp

AWS Redshift Intermediate

6.0/10

Years Exp

FAISS Intermediate

6.0/10

Years Exp

ChromaDB Intermediate

6.0/10

Years Exp

Pinecone Intermediate

6.0/10

Years Exp

LINUX Intermediate

5.4/10

Years Exp

Git Intermediate

5.4/10

Years Exp

Object-Oriented Design Intermediate

5.0/10

Years Exp

MCP Intermediate

5.0/10

Years Exp

Cd pipelines Intermediate

5.0/10

Years Exp

Work Experience

Data Scientist

Cognizant

Jan 2024 - Jan 2025

Engineered enterprise-grade RAG workflows over large-scale unstructured document repositories, streamlining automated data extraction and reducing domain query search times by ~40%. Architected state-based multi-agent orchestration pipelines using LangChain and LangGraph to automate dynamic query routing, contextual data lookups, and multi-step analytical reasoning. Optimized vector ingestion pipelines incorporating semantic text chunking, hybrid keyword/dense search, and metadata-driven filtering to boost context retrieval accuracy by 25%. Designed and deployed low-latency asynchronous microservices using FastAPI and Docker, securely integrating deployed models with core enterprise applications. Automated data preparation and vectorization pipelines leveraging AWS S3, Glue, and SQL, maintaining robust schema validation and data quality across batch workflows.