Heba Abdelhadi

About Heba Abdelhadi

I am an AI and Machine Learning Engineer with a strong foundation in data science, statistical analysis, and end-to-end ML model development. My career is built on transforming complex, unstructured data into solutions that support real business decisions. I bring a unique advantage through my Bachelor’s degree in Chemical Engineering, where I developed analytical thinking, scientific experimentation, process optimization, and disciplined problem-solving. Today, I apply these same principles to data analytics and machine learning, using a rigorous, data-driven approach to build predictive and intelligent systems.My project experience spans multiple domains, including heart disease prediction using CT scan images with neural networks and autoencoders, credit card fraud detection with highly imbalanced data, an IBM Watson–powered medical chatbot that uses NLP to support patient triage, a collaborative filtering wine recommendation system, and reinforcement learning models training Atari agents. I also work with modern LLM tooling such as Retrieval-Augmented Generation (RAG) pipelines, LangChain, FAISS vector databases, and FastAPI for deploying interactive AI applications and model inference APIs. These projects reflect my ability to collect, clean, explore, and model data while communicating insights clearly and designing experiments grounded in scientific methodology.Technical skills include machine learning, deep learning, supervised and unsupervised learning, CNNs, DQNs, NLP, RAG systems, LangChain, vector search with FAISS, Python, R, SQL, FastAPI, TensorFlow, Keras, Scikit-learn, Pandas, NumPy, Matplotlib, Seaborn, Docker, virtual environments, data preprocessing, feature engineering, model evaluation, and building scalable data workflows.My soft skills include analytical reasoning, scientific thinking, strong communication, cross-functional collaboration, adaptability, attention to detail, and ownership of complex challenges. I thrive in environments where innovation, experimentation, and continuous learning are valued.My concluding argument is simple: I combine the mindset of a scientist, the discipline of an engineer, and the capabilities of a modern AI practitioner. I build solutions that are technically sound, scalable, and directly aligned with real-world impact. I am seeking roles as an AI Engineer, Machine Learning Engineer, or Data Scientist where I can deliver intelligent, production-ready AI systems that drive smarter, data-informed decisions.

Experience

1. Data Scientist Machine Learning Engineer

   Qwasar Silicon Valley

   Jan 2023 — Present

   Developed AI-powered models for enterprise applications, including fraud detection, medical imaging, and recommender systems. • Built and optimized deep learning models using TensorFlow/Keras, leveraging CNNs, reinforcement learning, and autoencoders. • Designed end-to-end ML pipelines for model training, evaluation, and deployment in cloud-based environments.

Education

• Per Scholas

  Software engineer

• Qwasar Silicon Valley

  Data scientist and machine learning

• City College of New York

  Bachelor of Engineering (BE), Chemical Engineer

  2008 — 2011

• Oakland University

  Master of Artificial Intelligence, Artificial Intelligence

Skills

• Powerpoint
• Computer Skills: Microsoft Word, Excel, Powerpoint, Super Pro, Sap Core Qualitie
• Chemisry
• Time Management
• Multi Tasking
• Sap Products
• Teamwork
• Research
• Matlab
• Aiche & Sache Certifications: Chemical Process Safety, Runaway Reactions, Risk a
• Data Analysis
• Engineering
• Training
• Sap
• Microsoft Office
• Laboratory
• Leadership
• Organized
• Chemical Engineering