Data Analyst Class B

MATTHEW TOMBERS

Phone: 708-***-**** Email: ********@*****.*** LinkedIn: m_tombers GitHub: m_tombers

SUMMARY

Data Analyst technology enthusiast with a Bachelor’s degree in Computational Physics - Mathematics. Recently completed a Data Science fellowship; growing skills in data analysis, statistical modeling, Python, and SQL.

Leveraging experience in technical communication and a passion for metrics, performance, and tuning; I aim to land a role working in Data Analytics - Machine Learning - Software Development.

TECHNICAL SKILLS

Languages: Python (pandas, NumPy, Seaborn, Matplotlib, scikit-learn)

Machine Learning: Linear Regression, Logistic Regression, Decision Tree, RandomForest, Xgboost, Support Vector Machine, K-Means

Statistical Methods: Regression, Classification, Clustering, Statistical learning, Hypotheses testing

Predictive Modeling: Google Cloud Platform

Database Management: SQL

Data Visualization: Tableau

PROJECTS

Strawberry Classification Model

●Created an image classification model for strawberries using Google Cloud Platform.

●Labeled 400 images of strawberries class A (clear images - less leaves) or class B (blurred images - more leaves) and trained a classification model to predict the class given an unlabeled image.

●Model metrics: accuracy = 0.91, precision = 0.84, recall = 1

●Tools: Kaggle, Python (pandas, NumPy, Matplotlib), GCP Auto ML computer vision

Automated farming vs. Traditional methods

●Conducted an efficiency analysis to determine if automated Controlled Environment Agriculture (CEA) is more efficient than traditional farming methods.

●Using data from AutonomousGreenhouseChallenge2019 - Compared automated CEA vs. current commercial production methods of cherry tomatoes.

●Automated CEA consumed: 1.1% more electricity, 5.6% more CO2, 5.9% more water, 87.1% less heat, and produced 5.1% more fruit compared to the current commercial method.

●Tools: CEA Open Data, Python (pandas, NumPy, Matplotlib)

EXPERIENCE

Kaggle competition House Prices - Advanced Regression Techniques 2022

●Create a pricing model using provided housing data set

●Random Forest Regressor model Mean Absolute Error: 21,218

Kaggle competition Titanic - Machine Learning from Disaster 2021

●Build a model to predict the fate of passengers on the Titanic

●Random Forest Classifier model : 77.5% accurate

Data Science Fellow Springboard 2020 - 2021

●Data Analytics

●Machine Learning

●Python, SQL, statistics

EDUCATION

Illinois State University Normal, IL

Bachelor of Science in Computational Physics Mathematics minor

CERTIFICATIONS

Data Science Career Track Springboard 2021

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