Devendra Choudhary
Data Scientist
github.com/DevendraChoudhary1005 | candidates.intervues.club/u/devendra-choudhary
SUMMARY
Data Scientist and AI/Software Engineering professional with a strong foundation in machine learning, system design, and data processing. Experienced in building full-stack AI applications, automated trend analysis platforms, and cloud monitoring systems. Proven background in utilizing frameworks like PyTorch, TensorFlow, and FastAPI to deliver scalable technical solutions.
EXPERIENCE
AI / Software Engineering Intern
IntersElite
Oct 2023 – Dec 2023
- Designed and shipped a stock analysis platform using AutoTS and yFinance API to process 2 years of OHLCV data for surfacing price trends and market signals.
- Executed full build-test-deploy cycles across project lifecycles using agile sprint methodology.
- Collaborated with a cross-functional team through planning, code reviews, and iterative delivery.
EDUCATION
JECRC University, Jaipur, India · B.Tech · 2023 – 2027
Aditya Birla Public School · Class XII · 2022 – 2022
Padma Binani Public School · Class X · 2020 – 2020
SKILLS
Languages and Frameworks: Python, SQL, Jupyter Notebook, FastAPI, Flask, NumPy, pandas, PyTorch, scikit-learn, Streamlit, TensorFlow
Databases: PostgreSQL, pgvector, SQLite
Tools: AWS, Docker, Git / GitHub, MLflow, Plotly, Algorithms & Data Structures, OOP
PROJECTS
ClauseGuard — Multi-Agent RAG Document Assistant
Built a full-stack multi-agent RAG application for semantic search and Q&A over PDFs, combining FastAPI, LangGraph, and PostgreSQL with pgvector for cosine-similarity vector search. Architected multi-agent RAG workflows for semantic search and document Q&A over PDF files. Integrated PostgreSQL and pgvector for high-performance cosine-similarity vector retrieval. Containerized and deployed services using Docker, FastAPI, and Groq (Llama 3.1).
Python, FastAPI, LangGraph, Groq (Llama 3.1), PostgreSQL, pgvector, Docling, Docker
GitHub
ThreatVision — AI-Powered Cloud Security Monitoring System
Building a real-time cloud security monitoring platform using ML anomaly detection (Isolation Forest + UBA) to identify bruteforce attacks, unauthorised access, and malicious activity. Developed real-time cloud security monitoring pipelines using ML anomaly detection models such as Isolation Forest. Implemented User Behavior Analytics (UBA) to identify unauthorized access and brute-force attack attempts. Built interactive monitoring dashboards and REST APIs using Streamlit, FastAPI, and scikit-learn.
Python, scikit-learn, FastAPI, Streamlit, SQLite, Docker, AWS, REST APIs, Git
GitHub
AWARDS
Badminton State Level Team Leader, IBM Data Science Professional Certificate