My name is Kamaal Bartlett

About Me

Hello, I'm Kamaal Bartlett, a passionate data science graduate student at The University of Denver. My foray into the captivating world of data science unfolded after successfully completing my undergraduate degree in Accounting and Finance at Youngstown State University. Although I initially embarked on a career path in accounting and finance, the concept of "big data" had already piqued my interest during my college years.

While working in the realms of accounting and finance, I had the opportunity to witness firsthand the remarkable breadth and depth of the big data landscape. The sheer magnitude and potential impact of data-driven insights fascinated me, igniting a curiosity that led me to explore the exciting field of data science. This exposure served as a catalyst, driving me to delve deeper into the world of data, analytics, and the extraordinary possibilities they hold.

Fueling my passion for data science, I enrolled in a comprehensive data science bootcamp hosted by Springboard. The bootcamp provided me with an extensive toolkit and exposed me to a wide array of concepts, techniques, and methodologies. As I delved deeper into the program, I discovered my interest in Machine Learning and Artifical Intelligence applications.

After completing the bootcamp, I realized there was so much more to learn and in an effort to further expand my skills I decided to pursue my graduate degree in data science. I am eager to apply my knowledge to real-world challenges and make a meaningful impact in the field.

Beyond my professional pursuits, I am an avid learner and a dedicated problem solver. I am a big sports fan, a novice guitar player and a daring adventurer. I am driven by the potential of data science to transform industries and improve lives. By leveraging cutting-edge technologies and employing rigorous analytical techniques, I aim to uncover valuable insights and drive data-informed decision-making.

Join me on this exciting journey as we explore the boundless possibilities of data science together. Let's connect, collaborate, and pave the way for innovative solutions that shape our future.

NBA MVP Prediction

Github project files can be found here.

The NBA MVP Prediction project uses Python, Pandas, Seaborn, Matplotlib, Linear Regression, Random Forest Regressor, XGB Regressor, and, LGM Regressor to analyze NBA statistics and make predictions.

The data used in this project was scraped from the web in combination with a Kaggle dataset, after cleaning the data and finding correlations between statistical categories using a heat map, features were selected along with the target variable.

From here, the data was split into training and testing sets and trained on prior season data where the MVP winner was already known. After returning accuracy scores of over 60% across all models, the data scrapped from the web was put into the model and used to predict the 2022-2023 MVP winner.

Overall, this project required a lot of testing between the independent variables and hyperparameter tuning in order to return the most accurate results. In a project like this, the accuracy score is a very important measure as it tells us how many times the model can predict the correct winner for a given season based on the selected features.

Housing Forecast

Github project files can be found here

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Amazon Review

Github project files can be found here

This repository contains a comprehensive analysis of customer review data for a product listed on Amazon.

The main objective is to perform sentiment analysis on customer reviews to gain insights into their sentiments towards the product.

The project utilizes natural language processing (NLP) techniques and machine learning models to accurately predict the sentiment of reviews.

Most Recent Experience

Bootcamp Student
Springboard Data Science Career Track
October 2022 - June 2023
Remote
•500+ hours of hands-on course material
•1:1 industry expert mentor oversight
•Covered skills in Python, SQL, data wrangling, data visualization, hypothesis testing, and machine learning

Financial Analyst
The RFP Success Company
June 2022 - Present
Remote
•Interpret data, analyze results using analytics, research methodologies, and statistical techniques
•Find patterns and trends in analyzed data and Prepare reports and projections based on analysis findings
•Utilize software programs such SQL, SAS and Microsoft Excel to interpret and analyze large health care data sets
•Assist in the development of client communications, proposals, reports, spreadsheets, and presentations
•Collaborate with both small and large teams on project assignments

Accountant
Fairwind, Inc
September 2021 - June 2022
Miami, Florida
•Responsible for the accounts payable and accounts receviable process for Fairwind USA and Fiarwind Canada
•Prepare quarterly tax filings and annual state tax filing
•Prepare month-end financial statements, reconcile bank accounts and make adjusting entries
•Conduct analysis of purchase orders and invoices to guage company position on a month-to-month basis
•Process and analyze large sums of data using Microsoct Excel and Microsoft Dynamics NAV

Skills

Technical Skills: Python, Machine Learning, SQL, Data Analytics, Statistics, Mathematics, Big Data, Microsoft Excel, Hadoop, Financial Analysis

Soft Skills: Commmunication, Leadership, Teamwork, Problem Solving

Elements

i = 0;

while (!deck.isInOrder()) {
    print 'Iteration ' + i;
    deck.shuffle();
    i++;
}

print 'It took ' + i + ' iterations to sort the deck.';