07/14/2026 updated
100 % available
Data Science | Data Analyst | AI Engineer | Machine Learning & NLP Specialist | LLM & RAG Systems
varanasi, India
Only remote
B.Tech IIT RoorkeeAbout me
I am chandra kumar patel B.Tech graduated from iit roorkee having experience and skills in the field of AI/ML and data science and the thing which make s me unique is my dedication towards works through which i try my best to complete work before deadline
Application Programming Interfaces (APIs)Artificial IntelligenceData AnalysisConsultingData ArchitectureData Definition LanguageData IntegrationData Manipulation LanguagesData TransformationData Processing SystemsData SystemData Transformation ServicesData IntelligencePython (Programming Language)Machine Learning
Large Language Models & RAG Systems
Expertise in building LLM applications and Retrieval-Augmented Generation (RAG) systems, including RAG storage architecture managing documents, metadata, and embeddings using FAISS hybrid retrieval, as well as integrating Generative AI and NLP models for context-aware answer generation.
Python & FastAPI Development
Strong proficiency in Python-based development, including building FastAPI backends with structured REST APIs for file uploads, chat, and context retrieval, as well as developing data ingestion and normalization pipelines for diverse data formats.
Natural Language Processing & BERT
Hands-on experience with NLP pipelines and BERT-based classification, including intelligent interruption handling using BERT embeddings to classify user intent, keyword rules combined with semantic fallback achieving 90%+ accuracy, and speech transcription using Whisper.
SQL Analytics & ETL Pipelines
Building multi-layer SQL-based ETL pipelines with normalized schemas, strong data validation, advanced SQL queries to monitor stock, detect shortages, and creating dashboards and KPIs for inventory decision-making.
Machine Learning & Deep Learning
Practical knowledge of Machine Learning, Deep Learning, Transformers, PyTorch, Hugging Face, Scikit-learn, and Embeddings for building production-oriented AI systems and automation workflows.
Speech Processing & Audio Analytics
Development of AI-powered speech analysis systems evaluating pitch delivery using advanced audio analytics, multi-agent AI feedback, and automated speech transcription with confidence assessment through Whisper and emotion analysis.
Cloud & DevOps
Familiarity with AWS, Git, GitHub Actions, REST APIs, CI/CD pipelines, Docker, and Kubernetes for deploying and managing AI applications in cloud environments.
Databases & Vector Storage
Experience with MySQL, Vector Databases, FAISS, and ChromaDB for managing structured and unstructured data in AI-driven document intelligence solutions.
Frameworks & Libraries
Proficiency in FastAPI, LangChain, LangGraph, NumPy, Pandas, Scikit-learn, Librosa, and spaCy for building scalable AI and data science applications.
Expertise in building LLM applications and Retrieval-Augmented Generation (RAG) systems, including RAG storage architecture managing documents, metadata, and embeddings using FAISS hybrid retrieval, as well as integrating Generative AI and NLP models for context-aware answer generation.
Python & FastAPI Development
Strong proficiency in Python-based development, including building FastAPI backends with structured REST APIs for file uploads, chat, and context retrieval, as well as developing data ingestion and normalization pipelines for diverse data formats.
Natural Language Processing & BERT
Hands-on experience with NLP pipelines and BERT-based classification, including intelligent interruption handling using BERT embeddings to classify user intent, keyword rules combined with semantic fallback achieving 90%+ accuracy, and speech transcription using Whisper.
SQL Analytics & ETL Pipelines
Building multi-layer SQL-based ETL pipelines with normalized schemas, strong data validation, advanced SQL queries to monitor stock, detect shortages, and creating dashboards and KPIs for inventory decision-making.
Machine Learning & Deep Learning
Practical knowledge of Machine Learning, Deep Learning, Transformers, PyTorch, Hugging Face, Scikit-learn, and Embeddings for building production-oriented AI systems and automation workflows.
Speech Processing & Audio Analytics
Development of AI-powered speech analysis systems evaluating pitch delivery using advanced audio analytics, multi-agent AI feedback, and automated speech transcription with confidence assessment through Whisper and emotion analysis.
Cloud & DevOps
Familiarity with AWS, Git, GitHub Actions, REST APIs, CI/CD pipelines, Docker, and Kubernetes for deploying and managing AI applications in cloud environments.
Databases & Vector Storage
Experience with MySQL, Vector Databases, FAISS, and ChromaDB for managing structured and unstructured data in AI-driven document intelligence solutions.
Frameworks & Libraries
Proficiency in FastAPI, LangChain, LangGraph, NumPy, Pandas, Scikit-learn, Librosa, and spaCy for building scalable AI and data science applications.
Experience
Professional experience0 - 5 years
Freelancer since2026
Languages
EnglishFluentHindiNative speaker
Project history
Designing an automated financial modeling system to ingest multi-year statements from Excel and PDF inputs. Developing Python-based data ingestion and normalization pipelines to standardize diverse financial formats. Working with finance professionals to understand real-world chart of accounts and projection practices. Working on assumption-driven scalable Python scripts for financial forecasting and automation.
Developed an AI-powered speech analysis system evaluating pitch delivery using advanced audio analytics. Implemented multi-agent AI feedback providing diverse Shark Tank-style presentation evaluation perspectives. Automated speech transcription and confidence assessment through Whisper, pitch and emotion analysis. Technologies: NLP.
Built a personalized AI chatbot allowing users to upload notes and interact with them. Implemented the FastAPI backend with structured REST APIs for file uploads, chat, and context retrieval. Developed RAG storage architecture managing document, metadata, and embeddings using FAISS hybrid retrieval. Integrated Generative AI/NLP models for query understanding and context-aware answer generation.