Murali B

AI/ML Engineer, Data Analyst, or Software Engineer

Hyderabad, India 85 · Excellent

About

Fresher with strong Python, SQL, OOP, and DSA fundamentals, and hands-on experience shipping end-to-end AI/ML systems: deep learning with PyTorch, GenAI/RAG pipelines with LangChain and the Gemini API, and FastAPI backends deployed to production. Seeking an AI/ML Engineer, Data Analyst, or Software Engineer role.

Skills & Expertise (41)

Python Advanced

8.5/10

Years Exp

PyTorch Advanced

8.0/10

Years Exp

NLP Advanced

8.0/10

Years Exp

scikit-learn Advanced

8.0/10

Years Exp

Pandas Advanced

8.0/10

Years Exp

SQL Advanced

7.5/10

Years Exp

MySql Advanced

7.0/10

Years Exp

Git Advanced

7.0/10

Years Exp

Excel Advanced

7.0/10

Years Exp

Object-Oriented Programming Intermediate

6.5/10

Years Exp

Docker Intermediate

6.0/10

Years Exp

Data Structures & Algorithms Intermediate

6.0/10

Years Exp

Java Intermediate

5.5/10

Years Exp

Power BI Seaborn Matplotlib NumPy Tableau Postman Word GitHub PowerPoint Streamlit Cloud Render Outlook WebSockets GraphQL REST FastAPI Vector Embeddings Prompt Engineering Gemini API RAG Pipelines ChromaDB LangChain Classification Regression Transfer Learning Torchvision SQLAlchemy SQLite

Work Experience

Data Science Virtual Intern

CodSoft

Jul 2025 - Jul 2025

Built and evaluated a linear regression model for sales forecasting and a classification model for credit card fraud detection using Pandas and Scikit-learn, applying feature engineering and precision/recall analysis. Developed an Iris flower species classifier covering the full pipeline from preprocessing to model evaluation.

GenAI-Powered Data Analytics — Virtual Job Simulation

Tata Consultancy Services (via Forage)

Aug 2024 - Aug 2024

Validated and standardised 10,000+ row enterprise datasets in Python and Advanced Excel, achieving 100% data integrity for downstream use. Built AI-driven delinquency prediction models using regression and classification techniques; automated BI dashboards and reporting, cutting manual reporting effort by 40%.