**** **** ****** **. *****, OR, ***** 951-***-**** ac9d9v@r.postjobfree.com

Brandon Nelson

**** **** ****** **. *****, OR 97302

***** ***** **. ********, ** 92563

ac9d9v@r.postjobfree.com

http://willamette.edu/~bsnelson/ ~ https://github.com/bsnel21 EDUCATION

Bachelor of Arts in Computer Science;

Minors in Mathematics & Economics (3.3 GPA)

Willamette University. Salem, Oregon. Graduation Date: May 19, 2019 EXPERIENCE

Using Data Science in Baseball

● Implemented random forest, support vector machines, decision trees, and logistic regressions to predict future pitches

● Created pivot tables, data visualizations and ANOVA tests to provide useful feedback on tendencies between two seasons

Analyzing Crime in Los Angeles Kaggle Datasets

● Extracted powerful insights through descriptive statistics and box plots to give users recommendations of where to not park vehicles, the most common crimes in each city, and the sex distributions of victims. Natural Language Processing Project Handwriting Recognition

● Used logistic regression models to correctly identify handwritten numbers from the MNIST data set 96% of the time

The Complete SQL Bootcamp Udemy - Jose Portilla, Data Scientist

● Learned how to read and write powerful, complex queries to a database

● Concepts included: Fundamental & advanced statements, group bys, joins, database & table creation The Advancement of Statistics, Data, and Technology in Baseball

● Presentation for the University’s Math Colloquium; 100+ people in attendance including professors, math and computer science students, athletes, and staff. Learned how to communicate effectively to varying backgrounds.

Relevant Courses CS, Probability, & Statistics

● Data Science, Machine Learning, Data Structures, Analysis of Algorithms, Functional Programming

● Research and Design, Economic Statistics, Social Statistics, AP Statistics, Probability and Statistics, SKILLS

● Python

● R

● SQL

● PgAdmin

● Haskell

● Java

● LaTex

● XCode / Swift

● GitHub

Machine Learning: Decision trees, random forest, support vector machines, clustering, logistic regression Python Libraries: Pandas, Scikit-learn, Numpy, Seaborn, Matplotlib AWARDS / OTHER

● Nominated “Outstanding Student in Data Science” 2019

● National Honors Society 2015

● Invitation to speak at Math Colloquium 2018

● 1st Team Academics 2014 & 2015

1505 High Street SE. Salem, OR, 97302 951-***-**** ac9d9v@r.postjobfree.com

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