End-to-End Data Scientist and Software Engineer with a passion for solving complex problems and building impactful solutions. My critical thinking and problem-solving abilities were honed through the Iranian National Olympiad in Informatics, where I ranked among the top 70 out of 11,000 participants. I hold a Master's in Information Systems (MSIS) from Northeastern University and a Bachelor's in Software Engineering (BSSE).
- Proficient in C++, Java, and Python, with expertise in Machine Learning, Data Mining, Web Scraping, and Software Development.
- Skilled in Data Science, with experience in analyzing complex datasets, building predictive models, and creating actionable insights to drive decision-making.
- Experienced in web development technologies like JavaScript and React, creating dynamic and scalable applications.
- Years of hands-on experience, including roles as a Data Scientist and a Quality Assurance.
I'm currently working on ResuMatch.AI, an innovative platform that uses AI, web scraping, and microservices to empower job seekers with personalized resumes and real-time job postings. Check out the project below!
📫 Email: faridghr.cs@gmail.com
🔗 LinkedIn: linkedin.com/in/farid-ghorbanii/
Feel free to explore my projects and reach out to discuss collaborations or potential opportunities!
💼 Your AI-Powered Job Application Assistant
🚧 Currently Under Development 🚧
ResuMatch.AI is an innovative platform I am currently leading and developing to simplify and enhance the hiring process using AI, web scraping, and a robust microservices architecture.
- Personalized Resumes: AI-driven tailoring to specific job descriptions with OpenAI GPT models.
- Job Aggregation: Continuously updated job postings via Python-based web scraping from Indeed.
- Secure Microservices Communication: Token-based authentication for seamless and secure operations.
- User-Friendly Interface: Dynamic job search and application workflows built with Express.js and EJS templates.
- Streamlined job search process.
- AI-optimized resumes for improved compatibility.
- Scalable, secure architecture to meet diverse user needs.
Stay tuned for updates as the project evolves to empower job seekers with advanced tools for their career journeys.
🚀 Streamlining non-profit workflows with AI and automation!
This project automates client registration for Community Family Services of Ontario (CFSO), reducing manual effort by 70% and enhancing efficiency using:
- OCR for Card Verification
- Automated Payment Validation
- Real-Time Notifications powered by LLMs
- Flask Backend with JotForm Integration
📊 Impact: Faster response times, improved accuracy, and cost-effective solutions tailored for non-profits.
Tackling the challenge of credit card fraud detection with imbalanced datasets. This project explores the impact of data imbalance on analysis and evaluates the effectiveness of various classification models to enhance fraud detection accuracy and reliability.
A data mining project aimed at uncovering insights and patterns in the HorseColic dataset. By applying techniques such as data preprocessing, feature selection, and model training, the project improves prediction accuracy and uncovers key relationships within the data.
Predicting wireless account churn to help businesses retain customers. This collaborative project identifies key churn drivers and builds a machine learning model to predict churn, empowering proactive customer retention strategies to support revenue growth.
An advanced web scraping solution that systematically extracts comprehensive product data from Digikala, including detailed laptop specifications, and employs a robust machine learning model to accurately predict laptop prices based on user-defined configurations, offering a data-driven approach to e-commerce insights.
An insightful HR dashboard built with Tableau that visualizes key HR metrics, employee demographics, and salary trends. This project simulates real-world HR data analysis, empowering decision-makers with actionable insights for optimizing workforce management.
Two dynamic dashboards designed to help sales managers and executives dive deep into performance metrics, customer trends, and sales strategies, providing a data-driven foundation for business growth.
A captivating data visualization project that dissects Netflix's vast movie library through multiple dimensions—country filmed, release dates, genres, ratings, and top cast and directors—offering a comprehensive view of Netflix's entertainment landscape.
An in-depth analysis of Airbnb listings through advanced Tableau visualizations, uncovering key market trends, ideal investment hotspots, and strategies to maximize rental income, turning data into profitable business insights.
A practical exploration of design patterns applied to a restaurant ordering system. This project showcases how various design patterns—Singleton, Factory, Builder, Strategy, Composite, Adapter, Decorator, and Observer—can be used to tackle real-world software design challenges. The result is a flexible, scalable, and maintainable system that can evolve to meet growing business needs.
A Java Swing-based application that fosters a community-driven platform for book sharing. BookShare Hub enables users to lend and borrow books from one another, promoting a culture of literature exchange. It’s a seamless solution to bring people together around a shared passion for reading and knowledge.
A domain-specific chatbot application designed to assist users in car shopping, powered by Large Language Models (LLMs) for natural language understanding and vector databases for efficient data storage and retrieval. The project implements the Advanced Retrieval-Augmented Generation (RAG) method, enhancing the chatbot's ability to provide accurate, context-aware responses by combining generative AI capabilities with retrieved data. Additionally, the chatbot is fine-tuned with GPT-4o-mini to optimize performance for car shopping queries.
This project focuses on evaluating and improving the performance of the RAG pipeline. It includes a Python notebook and report, documenting the evaluation process and outlining strategies for enhancing the metrics of the RAG-based chatbot, ensuring more reliable and accurate results in real-world applications.
A domain-specific application leveraging the RAG methodology, combining Large Language Models (LLMs) and vector databases to deliver accurate, relevant responses. Built using Python and Streamlit for the front-end, this project showcases how Retrieval-Augmented Generation can be applied to enhance chatbot performance, providing users with personalized, context-aware interactions.
The AutoMailer application is a powerful, user-friendly tool designed to streamline the process of sending personalized emails to multiple recipients. It leverages CSV files to load recipient data and enables personalization of email content. The app integrates with Gmail's SMTP server to send emails, track progress with a progress bar, and handle errors, making it an efficient solution for mass emailing campaigns, newsletters, or invitations.
A Python project that provides a variety of creative image filters using the OpenCV library. Each filter applies unique transformations to the input image, resulting in visually striking and artistic outputs, perfect for learning and experimenting with image processing techniques.
A comprehensive collection of tutorials to help you master Pandas, the most widely used library for data manipulation and analysis in Python. This resource will guide you through various Pandas functionalities, enabling you to efficiently manipulate, clean, and analyze data.
Learn how to create stunning static, animated, and interactive visualizations with Matplotlib. This repository provides tutorials that will teach you to use Matplotlib to craft professional-grade plots, graphs, and charts, essential for data science and analysis projects.
A collection of tutorials designed to help you master NumPy, the cornerstone of scientific computing and data manipulation in Python. This resource covers fundamental operations and advanced techniques in NumPy, enabling efficient numerical computations and data analysis.
