Samuel Elijah Edwards

Computer Scientist @ U.S. Census Bureau


About Me

I am currently a Computer Scientist with a Bachelor’s degree in Data Science from the University of California, Berkeley. My academic background has equipped me with a robust understanding of data analysis, statistical modeling, and machine learning, along with proficiency in programming languages such as Python and R. I am driven by a deep curiosity for how data can reveal critical insights, inform strategic decisions, and address complex real-world problems. My role as a Computer Scientist has provided me industry experience in project management, systems design, and cloud computing.


I have gained practical experience through diverse projects involving data transformation, predictive modeling, and machine learning applications, where I demonstrated the ability to extract and communicate actionable insights from raw data. Additionally, my experience in STEM tutoring has enhanced my communication skills, enabling me to convey complex technical concepts effectively. Leadership roles have further developed my project management capabilities and strengthened my collaboration with multidisciplinary teams.


I am eager to leverage my technical expertise and analytical acumen to contribute to groundbreaking advancements in data science. My goal is to deliver impactful solutions that foster innovation and drive meaningful change within the industry.

Projects

Digit Recognizer

Developed a neural network to identify handwritten digits using a Kaggle dataset, marking my introduction to computer vision.

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Exo-planet Classification

Applied clustering techniques and a neural network to categorize exo-planets by size using NASA's exo-planet data, exploring hidden trends.

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Business Product Analysis

Cleaned and analyzed a raw Kaggle dataset, creating a Tableau dashboard to highlight product insights, focusing on data visualization.

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National Basketball Association (NBA) Research Project

Analyzed NBA census data (2004–2022) in a team, revealing a unique link between free throw percentages and stadium location through causal experiments.

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Digital Asset Analysis

Used R and logistic regression to predict product conversions (70% accuracy). Visualized findings in Excel and presented recommendations in PowerPoint.

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Stock Valuation Prediction Model

Built a Python model using the Google Finance API to forecast stock prices with 57% accuracy, improving it by incorporating news data for better insights.

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Customer Sales Segmentation Analysis

Performed sales segmentation using Python, SQL, and Excel, identifying consumer trends and seasonal purchasing behavior through clustering techniques.

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Resumé

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My Resume