PROJECT EXPERIENCE

Business Application Project — Team Development

.NET 6|ASP.NET Core|Angular|JWT Authentication

  • A comprehensive full-stack business application featuring secure authentication, role-based access, and dynamic user interfaces.

  • Designed and developed RESTful API endpoints supporting transactional operations, secure user workflows, and role-based access

  • Implemented JWT token-based authentication in ASP.NET Core to enable secure login, token issuance, and protected API routes authorization middleware

  • Integrated Angular frontend with secured APIs using token handling (login flow, token storage, route guards)

  • Built reactive forms and modular UI components to support dynamic user interactions and validation

  • Applied security best practices such as input validation, proper error handling (401/403 responses), and CORS configuration

Employee Management Platform — Full Stack System

NET 8|ASP.NET Core|Angular|NgRx|Oracle|Dapper

  • Enterprise-grade employee management system with robust data workflows and centralized state management.

  • Designed and implemented REST APIs following layered architecture to ensure scalability and maintainability

  • Integrated Oracle stored procedures using REFCURSOR outputs to support enterprise data workflows

  • Improved data access performance using Dapper

  • Built Angular UI with centralized state management using NgRx to ensure predictable data flow

  • Implemented validation, error handling, and consistent API contracts

  • Documented APIs with Swagger to support testing and developer onboarding

  • Diagnosed and resolved full-stack issues including CORS configuration, API routing, and database connectivity

  • Applied dependency injection to decouple components and improve testability

  • Wrote unit tests validating service behavior and edge cases

  • Managed version control workflows using Git

Data Analytics Project — Dataset Cleaning & Exploratory Analysis

Python | Pandas | NumPy | Matplotlib

  • Loaded and cleaned a real-world audiobook dataset containing text, rating, price, and duration data and standardized author and narrator fields by removing inconsistent prefixes and handling missing values.

  • Parsed rating counts, duration (converted hours/minutes to total minutes), price, and release dates into analysis-ready formats.

  • Generated missing-value reports and duplicate detection logic using key identifiers (title, author, narrator).

  • Conducted exploratory data analysis (EDA) with summary statistics and histogram visualizations.

  • Produced a fully cleaned dataset (audible_cleaned.csv) for downstream modeling or BI reporting