Sharon X. Tan

** ****** ******, **** ******** NJ 07034 973-***-**** acyjmw@r.postjobfree.com

OBJECTIVE

I am seeking an entry level data analyst position with a company that enables personal growth in analytics or programming skills.

EDUCATION

Montclair State University Montclair, NJ

Master of Science (Statistics) Graduated: December 2016

Cumulative GPA: 3.90 (Dean’s List)

Bachelor of Science (Math Education K-12) Graduated: May 2014

Cumulative GPA: 3.84 (Dean’s List)

Awards/Scholarships: Robert Garfunkel Mathematics Fund, John C. Stone Award

WORK EXPERIENCES

Bergen Community College Lyndhurst, NJ

Adjunct Professor September 2016 – December 2016

Design lessons that implement the use to technology such as MyMathLab and Smart Board and accommodate the needs of students with disabilities

Attend professional development workshops

Montclair State University Montclair, NJ

Adjunct Professor July 2016 – August 2016 and May 2015 – June 2015

Cooperated with another adjunct professor to teach a fundamental Algebra course

Provided one-on-one attention to students, while maintaining overall focus on the entire group to help students to complete course objectives and pass the course

Graduate Assistant/ Professional Tutor September 2014 – Present

Conduct lectures in Algebra and Statistics using own lesson plans to help students complete the course

Offer one-on-one instruction to students who need additional help in Algebra, Calculus and Statistics

Support the Math Course Coordinator by grading quizzes and projects

SCHOOL PROJECTS

Data Mining Completed: May 2015

Utilized R to analyze dataset related to number of applications different colleges received and determine the best data mining method to use for the dataset

Implemented data mining method such as regression tree, boosted regression tree, and linear regression and concluded that boosted regression tree and linear regression to be the more appropriate methods to use

Used the mean square error to determine that acceptance and enrollment rate significantly predicted the number of applications received

Multiple Linear Regression Analysis on Cereal Prices Completed: May 2015

Predicted cereal prices based on variables such as net weight, sugar and fiber content, and brands and examined possible relationships among variables

Obtained multiple regression models using SAS and selected the best model through variable selection method

Utilized regression results to determine that none of the variables were significant predictors of cereal prices

Missing Data Analysis regarding Drug Abuse and Violence Behaviors Completed: September 2014

Imputed missing values on real life data and performed linear regression on the imputed dataset to determine significant variables that contributed to violence behaviors

Eliminated insignificant variables based on regression results and drug use, tobacco use, family conflict and assertiveness were shown to contribute the most to violence behaviors

SKILLS

Certified SAS Base Programmer

Proficient in R, SAS, JMP and Microsoft Office and familiar with MySQL

Fluent in English, Mandarin Chinese and Cantonese

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