Hey, I'm Charles

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About Me

I am an enthusiastic data scientist who is deeply passionate about diving into code and fully immersing myself in the process of building something remarkable out of nothing. Throughout my journey, I have primarily been self-taught, fueled by an unwavering passion for the industry. I firmly believe that the vastness of knowledge in this field is boundless, and that realization is what truly excites me. The prospect of constant learning and discovering better approaches to problem-solving fuels my drive to excel. I am always eager to embrace fresh challenges and contribute to a shared objective with my expertise.

  • Languages
    Proficient in Python, Swift, C#, HTML5, CSS, SCSS, and Javascript.
  • Data Science and Machine Learning
    Expertise in Panas, PySpark, TensorFlow, Numpy, Jupyter Notebook, Jupyter Lab, Lambda, and AWS.
  • DevOps and Cloud
    Experience with Docker, AWS, and Apache Airflow.
  • Data Visualization
    Skilled in Tableau and Microsoft Excel.
  • Version Control and Collaboration
    Proficient with Git and GitHub.
  • Front-End Frameworks
    Command over jQuery.
  • Web Scraping
    Proficiency in BeautifulSoup.
  • Mobile Development
    Experience with Apple technologies and Swift.
  • Data Analysis and Manipulation
    Expertise in Pandas and NumPy.
  • Database Management
    Experience with MySQL, PostgreSQL, and MongoDB.
  • Back-End Frameworks
    Hands-on experience with Django.
  • Statistical Analysis
    Knowledge of SciPy, Statsmodels, and Scikit-Learn.
  • Collaboration and Communication
    Proficiency in platforms like Slack, Discord, and GitHub Pages.
  • Interactive Web Experiences
    Experience with Canvas.
  • Real-Time Data Processing
    Expertise with Kafka.
  • Markdown and Documentation
    Experience in using Markdown for documentation.
  • Operating Systems
    Familiar with Ubuntu as an operating system.
  • Database Querying
    Strong command of SQL.
  • R Programming
    Knowledge of R for implementing statistical models and visualization techniques.
  • Intelliware Solutions - Data Scientist (2020 - Present)
    Developing AI-driven solutions, using AI and Machine Learning to extract valuable insights, fostering innovation across various industries.
  • Contract Data Engineer (2020 - 2022)
    Honing skills in Python development within the Django framework, managing ETL processes on large data lakes, establishing data pipelines, and message aggregation using AWS, PostgreSQL, and SQL.
  • 4s Pipeline Services - Project Manager (2019 - 2020)
    Managing pipeline construction and directional drilling services, introducing data analytics into the project management process, and handling resource allocation and budget constraints.
  • United States Air Force - Various Roles (2010 - 2017)
    Performing various management roles including Security Operations, Tactical Response Force, Nuclear Security Operations, and Logistics and Operations.
  • Harvard Extension School - Master's degree, Data Science (current)
    I am currently enrolled in the Master's in Data Science program at Harvard Extension School, where I am gaining hands-on experience in advanced programming languages and tools. The program is sharpening my analytical skills through courses that cover data modeling, machine learning algorithms, and artificial intelligence techniques. I am also developing business intelligence acumen, learning to translate complex data into actionable insights. As part of the curriculum, I am working towards a capstone project that involves real-world data science applications in collaboration with industry partners. This comprehensive program is equipping me with the multidisciplinary skills required to excel in various data science roles.
  • Codeup - Data Science (2021)
    Fully-immersive, project-based 22-week career accelerator that provides students with 670+ hours of expert instruction in applied data science. Students develop expertise across the full data science pipeline (planning, acquisition, preparation, exploration, modeling, delivery), and become comfortable working with real, messy data to deliver actionable insights to diverse stakeholders.
    Skills: Python - SQL - Pandas - Spark - Matplotlib - Seaborn - Machine Learning - Natural Language Processing - Data Storytelling - Github - Jupyter Notebooks - Applied Statistics - Anomaly Detection
    Codeup’s programs are approved and audited by the Texas Workforce Commission as well as the US Department of Veterans Affairs.
  • University of Arizona - Bachelor's degree, Psychology (2019)
    Studied business systems development, information assurance and security, project planning and implementation, database concepts, principles of supervision, leadership and motivation, criminal justice, human formal and informal logic, industrial and organizational psychology, abnormal psychology, statistics for the behavioral and social sciences, and theories of personalities.
  • Non-Commissioned Officer Academy - Operations Management and Supervision (2015)
    Training on advanced management and supervisor duties, encompassing performance evaluations, conflict resolution, mentorship, task-prioritization, team management, public speaking, and effective oral and written communication.

My Work

Bitcoin Price Prediction

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Bitcoin Price Prediction Time-Series Project

This endeavor aims to identify cyclical patterns and predict Bitcoin's price with a higher accuracy than baseline models. The dataset, sourced from Kaggle, encompasses Bitcoin's open, high, low, and closing prices, alongside transaction volumes. Key deliverables include a well-documented Jupyter notebook, a comprehensive README, and Python modules that facilitate data acquisition and preprocessing.

American Sentiment Analysis

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Discovering drivers of Americas prospective thinking

The project uses American Trends Panel Datasets to predict American sentiments, especially pessimism about the future. Data from Pew Research covers diverse aspects of American life, including demographics. Analysis revealed that public education and U.S. economics are key drivers of pessimism, while age and income aren't significant.

NLP - Github Lang Prediction

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Natural Language Processing - Github Coding Language Prediction

The "Natural Language Processing - Github Programming Language Prediction" project aims to predict a repository's programming language based on its README file content. By scraping 30,000 GitHub README files and primarily focusing on Javascript repositories, the team developed a model achieving over 94.8% accuracy in predictions. The project encompasses the entire data science pipeline, including data acquisition, preprocessing, exploration, modeling, and presentation.

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