Welcome to My Portfolio!
I’m a final-year Computer Science student passionate about solving data problems using Python, SQL, and Power BI. 📈
I’ve built several end-to-end projects and aspire to work in data analytics and AI.🔍
About Me
I’m a Computer Science (Data Science) undergraduate from NIET, with a strong passion for uncovering insights from data to solve real-world problems.
My journey began with a curiosity for numbers and patterns, which evolved into hands-on experience through academic projects and self-driven learning.
I’ve successfully completed several data analysis projects that reflect my analytical thinking, technical skills, and commitment to continuous growth.
I enjoy transforming raw data into actionable insights. Explore my portfolio to see how I solve complex data challenges with practical, results-oriented solutions.
Skills & Technologies
Programming Languages
Python
SQL
Java
Data Visualization
Power BI
Tableau
Matplotlib / Seaborn
Databases & Tools
MySQL
MongoDB
Analytics & ML
Machine Learning
Statistical Analysis
Data Mining
Business Tools
Advanced Excel
Google Analytics
Cloud & Other
AWS S3
Git / GitHub
Kubernetes
Featured Projects
Comprehensive analysis of the Atliq Hardware Sales , focusing on market penetration, growth opportunities, and competitive landscape for strategic decision-making.
Key Achievements:
- Identify high and low-performing cities based on profit margin
- Track revenue and profit changes from 2017 to 2020
- View revenue and profit contribution by market
- Analyze revenue and profitability by customer.
Built an interactive news research assistant using Google Gemini and Streamlit. RockyBot allows users to extract, analyze, and query multiple news articles intelligently using LLM-driven question-answering.
Key Features:
- Multi-article processing and content extraction via scraping and LangChain loaders
- Semantic search using vector embeddings (FAISS)
- Natural language Q&A with contextual memory and random prompts
- Visual metrics dashboard and quick insights with chat history
Comprehensive analysis of customer spending behavior and demographics to guide credit card product development and marketing strategies for a leading bank.
Key Findings:
- Credit cards are the preferred payment method for customers
- Major spending in bills, groceries, electronics, and health
- Male and married customers show highest spending patterns
- 25-45 age group represents the primary target demographic
In-depth Python analysis of hotel performance data to identify revenue optimization opportunities and develop data-driven strategies for competitive advantage.
Project Highlights:
- Comprehensive data cleaning and transformation processes
- Advanced statistical analysis and visualization
- Revenue optimization and occupancy rate analysis
- Customer segmentation and behavior insights
Let's Connect!
I'm always excited to discuss data projects and opportunities