Alexis Ding

Logo

Graduate Student at Northeastern University

Seattle

Alexis DING

(617) 755-5315           ding.ziha@husky.neu.edu

IT Skills

Java; Python, scikit-learn, pandas, Matplotlib; SQL, NoSQL, ETL(SSIS), Tableau, PowerBI; JavaScript, React, Node.js; AWS Glue, Athena, S3; Microsoft Excel

EDUCATION

Northeastern University

Seattle, WA

Master of Science, Information Systems – GPA: 4.00/4.00

Sep.2017 – Dec.2019

·       Main Courses: Program Structure and Algorithms; Database Management and Database Design; Web Development Tools and Methods; Data Science Engineering Methods and Tools; Business Analysis, etc.

Boston University

Boston, MA

Master of Education, TESOL (Teaching English as a Second Language) – GPA: 3.93/4.00

PROFESSIONAL EXPERIENCE

Lead Graduate Teaching Assistant

Seattle, WA

Database Management and Database Design

May 2019 – present

·       Provided support and guidance to 117 students 20 hours/week

·       Collaborated with the professor to monitor and track students’ performance

·       Assisted professor with Database design and SQL query assignments and quizzes grading

·       Led the TA team to support with the course contents and student inquiries

PROJECTS

Game of Hearts

Fall 2017

·       Created a UML class diagram based on the game rules in OOP design pattern

·       Implemented all the classes, game logics and players’ total points calculation in Java

·       Implemented functions to optimize card playing order to increase players’ winning rate

Guess the Word Game

Spring 2018

·       Designed a single-page web-based guessing word game using React components and npm modules

·       Created an Express server to run the web service which selects a secret word from the word list

·       Implemented algorithms to find out the secret word efficiently using JavaScript, and designed the layout and web style using HTML and CSS

F2E Database Design

Fall 2018

·       Created an Entity Relationship Diagram using Microsoft Visio with crow’s foot notation

·       Created schemas, tables, views and constraints to make sure each student can only apply once using Microsoft SQL Server and SQL Server Management Studio

·       Created triggers for automatic data updates and encrypted PII data by creating encrypted keys

·       Imported dataset from SQL server and generated data analysis reports using PowerBI, created visualizations using views showing selected student ratios, bank transactions, and students and donors distribution views

Credit Card Fraud Analysis and Detection

Spring 2019

·       Performed data preprocessing and feature transformations for features of Time and Amount, added new features which calculated seconds between the time when the transaction occurred and last fraud/ zero amount occurred

·       Applied under-sampling and over-sampling approaches for an unbalanced dataset to resample the under-represented classes so that all classes have a similar amount of data

·       Fit Logistic Regression models, Random Forest models and Gradient Boosting models using Python scikit-learn libraries, finding out Logistic Regression models best fit the data with an AUC of 0.979 and a Log Loss of 0.0038

·       Predicted credit card fraud for test set using selected models, getting the test set Log Loss of 0.0034

King County House Price Analysis and Prediction

Spring 2019

·       Performed data cleaning and preprocessing, log transformations for skewed features, outlier elimination and feature encoding for categorical features including Zipcode and Month

·       Applied validation set and forward stepwise selection approaches to select best features and models

·       Fit Linear Regression models with selected features using Python aligned with Numpy, pandas and scikit-learn libraries, getting the R-squared of 0.854, and RMSE of 0.20

·       Predicted house price for test set using selected features and models, getting the test set RMSE of 0.18

Skills

  • Java
  • Python
  • SQL
  • Updated 1 year ago

To contact this candidate email ding.ziha@husky.neu.edu

Contact using webmail: Gmail / AOL / Yahoo / Outlook

X