Brandon Thoma
CELL 510-***-**** • E-MAIL ac2eym@r.postjobfree.com • LINKEDIN https://www.linkedin.com/in/brandon-thoma EDUCATION University of California, Los Angeles, Los Angeles, CA September 2012 – June 2017 B.S. Applied Mathematics, June 2017
GPA: 3.7 / 4.0
Statistics GPA: 3.8 / 4.0
Relevant Coursework Completed: Data Analysis and Regression; Mathematical and Computational Statistics; Mathematical Modeling; Introductory R; Probability; Optimization Statistics; Experiment Design; Data Mining and Machine Learning; Statistical Research; Introductory C++; Econometrics EXPERIENCE Data Analyst, SoCalGas, Los Angeles, CA June 2016 – August 2016
• Improved the ability to answer complex, relevant business questions, such as customer demand by geographic location, by combining and cleaning multiple company Excel data sets in R.
• Reduced district servicing costs by increasing customer order prediction accuracy by 10-40% depending on order type, by creating an ensemble model of multiple machine learning models.
• Reduced time to generate customer forecasts by building a single function that utilized only 3 inputs to generate Excel forecast spreadsheets quickly and efficiently.
• Reduced the price negotiation time with regulators by improving prediction reliability through streamlining the prediction methodology from 10+ methodologies to a single methodology.
• Effectively communicated the benefits of the new forecast methodology to coworkers by explaining complicated statistical concepts in easy-to-understand terminology. Data Quality Controller, Zoosk, San Francisco, CA July 2014 – August 2014
• Improved customer satisfaction by adding additional key words to each database entry which increased the company’s matching algorithm’s accuracy.
• Improved the reliability of dating matches by improving the consistency of sources used to inform each entry’s description, through reducing 100+ sources down to fewer than 10 sources. Operations Assistant, The Millennium Group, San Francisco, CA July 2014
• Improved employee satisfaction with accurate and timely delivery of mail and packages as well as with service requests.
PROJECTS Technical:
• LA Fire Department Predictive Model (2017): Placed 1st out of 38 teams in Machine Learning class final project to predict Los Angeles fire department response times from public data.
• Expedia Travel Destination Temperature Visualization (2017): Created insightful Tableau heat maps utilizing Expedia travel data, and additional supplemented data from NOAA, to show differences between home state and travel destination temperatures, at Datafest UCLA 2017.
• LA Car Sales Visualization (2016): Created ggplots and ggmaps visuals to see the relationship between LA zip code and the brand of car purchased using IRS and google map data. SKILLS Technical:
• R (advanced); C++ (proficient); Python (proficient); SQL (proficient); Stata (proficient)
• Tableau (proficient); R-markdown (advanced); Excel (proficient)
• Amazon Web Services (AWS); H2O
• ML Algorithms: KNN, Regression, Trees, Random Forest, Gradient Boosting, SVM, Neural Networks, Ensembles, K-Means Clustering, EM Algorithm, PCA, PCR, PLS, Naïve Bayes, etc.