I'm a full stack AI developer, data scientist, and project manager. I am passionate about asking creative questions and using data to solve problems and reveal insights. I find it intriguing that human behavior and processes can be explained with algorithms. I am currently passionate about the new frontier of implementing AI solutions like LLMs in healthcare and research!

• Programming Languages: Python, R, SQL
• AI Techniques: LLM/SLM Fine Tuning, RAG, Synthetic Data Generation (VAE), Recommender Systems, Machine Learning
• Libraries: PyTorch, Keras, TensorFlow, ScikitLearn, SQAlchemy, NLTK, Tidyverse, Caret, Car, e1071
• Tools: Git, MySQL Workbench, R Studio, Jupyter Notebook
• Statistics: SAS, SPSS
• Data Vis/Dashboards: Tableau, Power BI, R Shiny
• Front End: Streamlit, PyQt5
• Cloud: AWS, GCP, Microsoft Azure
• Back End: Database Engineering, ETL, APIs
• Replicability & Full Stack Integration: Docker, Kubernetes

• Long COVID - Developed and evaluated models using 50 biopsychosocial features to classify long COVID diagnosis and predict cognitive complaint severity. Analyzed long COVID biotypes using k-means clustering of symptom profiles.
• Gender Gaps in Clinical Trials - Use natural language processing (NLP) of registered clinical trial descriptions (clinicaltrials.gov API) to assess differences in sex representation using classification model coefficients.
• Participant Dropout Factors - Created a decision tree classifier to identify demographics of participants likely to drop out of online research.
• COVID Economic Database - Created an ETL pipeline of covid-related, global, macroeconomic data.
• Pharmaceutical Drug Surveillance - Created an ETL pipeline of adverse drug event information to create a database that supports machine learning objectives, dashboarding, and model deployment via Streamlit application.
• Political Discourse Sentiment Analysis - Leveraged AWS cloud computing and natural language processing to capture public sentiment of presidential candidates from Twitter tweets and New York Times article comments.

• Master of Science in Applied Data Science, University of San Diego
• Bachelor of Science in Psychology/Biological Science, San Jose State University
• Associate of Arts in Social and Behavioral Sciences, Moorpark College

• LinkedIn: (https://www.linkedin.com/in/halee-staggs/)

• Professional Interests: Machine learning, data engineering
• Hobbies: Weight lifting, pilates, traveling, spending time with my dog, Luna :)

Feel free to reach out if you want to collaborate on a project or just want to connect!

"You cannot get clean in a dirty shower."