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Omar Mnfy

Computer Science & Data Science Sophomore at Pitzer College in Claremont, CA

  • I’m currently looking for summer 2025 software engineering, data analytics/engineering, or product management internships (Mid-May — Mid-August).
  • This Summer, I worked as Data Analyst at W.M. Keck Science Research Center working on d developing a power-law fit algorithm in MATLAB and cleaning meta data for visualization and optimizing code improving computation power.
  • After my research during the summer, I interned at WholeRen Education as a Data Engineer, directing AI product that helps international students on F1 visas find jobs with sponsorships. I also advocated and led research on a paid subscription business model for schools’ career offices.

Skills and Coursework:

  • Coursework: Data Structures and Algorithms, Foundations of Data Science, Linear Algebra, Multivariable Calculus, Statistics, Data Science Ethics, Introduction to Computer Science
  • Fellowships: Randall Lewis Center for Innovation and Entrepreneurship, Headstarter AI, Boulevard Fellowship
  • Programming Languages: Python, MATLAB, JavaScript, C/C++, SQL, HTML/CSS, R
  • Libraries: pandas, NumPy, Matplotlib, scikit-learn, Keras, TensorFlow, OpenCV, YOLO, Simulink, dplyr, ggplot2y
  • Frameworks: React, Node.js, Bootstrap, Flask, JUnit, WordPress, Material-UI, FastAPI, CUDA
  • DevOps and Infrastructure: Git, Amazon Web Services (AWS), Google Cloud Platform, Microsoft Azure, Linux
  • Technologies: Power BI, Apache Spark

Omar Mnfy's Projects

finetune-llama3-using-direct-preference-optimization icon finetune-llama3-using-direct-preference-optimization

This repository contains Jupyter Notebooks, scripts, and datasets used in our finetuning experiments. The project focuses on Direct Preference Optimization (DPO), a method that simplifies the traditional finetuning process by using the model itself as a feedback mechanism.

power-law-fit-distribution-matlab icon power-law-fit-distribution-matlab

This repository provides MATLAB implementations of plfit and plpva functions for fitting power-law distributions to empirical data using maximum likelihood estimation (MLE) and statistical goodness-of-fit tests. These tools accurately model complex systems with significant tail behaviors, common in fields like physics, biology, and economics.

pricewise-web-scraper icon pricewise-web-scraper

Build an eCommerce price tracker using Next.js and Bright Data's webunlocker. This tutorial covers web scraping, cron jobs, and email notifications, helping users track product prices and availability. Perfect for beginners, it features a user-friendly interface with carousel, search, and alerts.

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