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Location:
Glendora, CA, 91741
Posted:
April 08, 2022

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Resume:

Sean Gao

Legal Name: Yuxiang Gao

github.com/seangao14 adqqcg@r.postjobfree.com https://www.linkedin.com/in/seangao14/ SKILLS

Programming

• Proficient: Python

• Intermediate: R, SQL, VBA

• Familiar: C++, Java

MISC

• Data Processing/Retrieval

• Database

• Machine Learning

• Jupyter

• LaTeX

• Tableau

• Git/GitHub

• Excel

• Typing: 100+ WPM

• Chinese: Fluent

COURSEWORK

• Stochastic Processes

• Time Series

• Maths of Financial Instruments

• Statistical Data Science

• Statistical Machine Learning

EDUCATION

UNIVERSITY OF

CALIFORNIA,

SANTA BARBARA

Statistics and

Data Science BA,

Philosophy BA

Graduating Summer 2022

Santa Barbara, CA

HOBBIES

• PC Gaming

• Philosophy

• Rock Climber (click me)

• Speed Cuber (10.50 Personal Best)

• Competitive Tetris (95th percentile

of global competitive Tetris players)

WORK EXPERIENCE

HOMESITE INSURANCE Actuarial Intern - Reserving

Jun 2021 – Sep 2021 Remote

• Created a Python notebook for automated loss development modeling using various probability distributions such as Loglogistic and Weibull and the Chainladder Python library

• Created a Tableau dashboard for loss ratio report using data from an Amazon Redshift server

• Completed LDF (Loss Development Factor) reports for various lines of insurance, including LDF selection

WAYFURB Data Analyst/Information Technologies

Nov 2020 - Jan 2021 El Monte, CA

• Modeled depreciation of PC components using web-scraped data and machine learning models to price trade-ins

• Wrote a Chrome Extension to automate and streamline and speed up the shipping label printing/organization process

SANTA BARBARA CITY COLLEGE Assistant Baseball Data Analyst

Oct 2020 - May 2021 Remote

• Automated statistical calculations by programming spreadsheets (with both formulae and VB)

• Optimization of pitches given different pitchers, types of pitches, types of batters, etc.

PROJECTS

CLAIRVOYANCE Liquid Hacks 2020, Machine Learning

• Predicts the win probability at any given point in League of Legends matches with a precision score of 82%

• Used the Riot Games API to gather data for training

• Deployed a PyTorch neural network to a web app built using Flask, NginX, and Apache

REDDIT NLP Machine Learning

• Predicts the number of comments given any r/Askreddit question

• Used the Reddit API to fetch data from nearly 1 million posts

• Processed text data into computer readable dataframes

• Used techniques such as K-fold cross validation to select the best model for the data



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