Hi! I'm Zade, let me help you with your
The technical know-how to make your data shine
About Me
With a solid foundation in Physics, Mathematics, and Astronomy from my undergraduate studies, complemented by a Master of Science in Data Science, I bring a unique blend of analytical rigor and technical expertise to the table. My experience in leveraging Python development, database architecture, and data analytics enables me to uncover insights and drive impactful decisions. Let's connect and discuss how I can contribute to your data-driven initiatives!
Resume
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Zade Alfalah
US Citizen | (715) 797-5940 | Eau Claire, WI | zadealfalah@gmail.com
EDUCATION
University of Colorado, Boulder, CO
MS, Data Science - 3.96 GPA, Dec. 2022
BA, Physics, Mathematics, Astronomy, Jan. 2020
WORK EXPERIENCE
Legrand, Eau Claire, WI
Data Analyst, Jun. 2023 - Dec. 2023
Developed models and forecasts for stocking predictions
Led weekly strategy discussions based off of created models and analysis
Built document ingestion pipelines automating previously manual tasks, saving over $30,000/yr
Designed and deployed sales dashboards using Power BI
Introduced MySQL architecture reducing complexity and cost of analysis
Laboratory for Atmospheric and Space Physics, Boulder, CO
Junior Data Scientist Sep. 2017 - Dec. 2019
Architected ETL pipelines for processing large quantities of imagery data
Optimized imagery analysis scripts, reducing compute times by 22%
Built visualizations for conference presentations utilizing seaborn and matplotlib>
Onboarded junior scientists utilizing self-created documentation
PERSONAL PROJECTS
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Automated Web Scraping and Job Posting Analysis
Developed and maintained scalable backend for the project pipeline, built on AWS and Docker, running on ECS clusters
Integrated open-source LLMs (BERT, Llama) for text classification and entity recognition
Employed OpenAI API for zero-shot results, reducing costs
Used Ray/Anyscale for distributed training with MLFlow
Created API with FastAPI for speedy and efficient querying of model
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Custom Retrieval-Augmented Generation (RAG) Chatbot
Built a chatbot to help answer questions about books in my library
Utilized Langchain with Chroma for vector storage and Ollama as a platform
Integrated open-source LLMs (Mistral, Llama 2) incorporating prompt engineering for best results
TOOLS
Languages: Python, SQL, R, Bash, Git, JavaScript
Software: AWS, GitHub/GitLab, MySQL, Jupyter, MLFlow, Docker, ArcGIS, Tableau, Power BI, Excel
Libraries/Frameworks: Pandas/NumPy, NLTK/Spacy, XGBoost, PyTorch, TensorfFlow/Keras, HuggingFace, scikit-learn, Selenium, Airflow, Scrapy, OpenCV, Snowflake, FastAPI, Langchain, Terraform