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DU

Pham

Data Analyst

Profile

An applied mathematician who is passionate about Data Analysis and has experience collecting, transforming, and organizing data for analysis to help make informed decisions including data SQL queries from Google Cloud Storage and data wrangling. Excellent understanding and proficiency of platforms for effective data analyses, including SQL, spreadsheets, Tableau, Python, and R. Strong communication, organizing, and excellent analytical skills.

 

Excellent ability to sift through information and distill it down to easily understandable lessons and research work presentations.

 

Enjoying collaborating as a team member or a lead; productive in working independently. Ready and eager to join your data science team.

Contact

PHONE: 812-320-1882

 

WEBSITE: https://dxpham.github.io/

 

EMAIL: dxpham@gmail.com

data analytical skills

Data analysis, data cleaning, data visualization

Data-driven decision making

Effective presentations

Descriptive and Inferential Statistics

Linear/Logistic Regressions

R, Python programming

Calculation and analysis in SQL, spreadsheets

Machine learning: Mxnet, Tensor Flow

 

EDUCATION

 

Coursera 2021, Online

06–07/2021: Google Data Analytics Certificate.View Certificate

05–06/2021: Statistics with Python Specialization.View Certificate

07/2021–current: Data Visualization & Dashboarding with R Specialization.               

06–06/2021: Calculating Descriptive Statistics in R.View Certificate

 

Udemy 2021, Online

04/2021: Statistics for Science and Business Analysis.           View Certificate

 

Indiana University – Bloomington, Indiana

08/2001–05/2007: Ph.D. in Applied Mathematics with minor in Scientific Computing.

WORK EXPERIENCE

Data Science: Github Portfolio

 

Project 1: Top US Baby Name Animations. This work is in R. I collect the data set usa_names from Google Cloud by making SQL queries on the Google Cloud SQL Server. Besides the usual distribution and box plots of the top names over the year, I make several line and point animations of the names to see their changes in popularities over the years. I upload the dashboard of the animations on the Shiny server, please click here to see the online dashboard on the Shiny server.

 

Project 2: Bike Ride Share. In this project, I perform a data analysis process for the table data files at Cyclistic, a bike-share company in Chicago. The techniques include merging data files, data wrangling, and analyzing. The goal is to differentiate how casual riders and annual members use the bikes differently so that the team can come up with appropriate strategies to maximize the number of annual memberships. Here is my R notebook of the project.

 

Project 3: Predicting Tinanic Survivors. This is a Python notebook of my Kaggle competition in 2018, Machine Learning from Titanic Disaster. I used a three-layer neural network to predict the survivals at an accuracy of 85.4%. The result performed better than the traditional statistical methods.

 

Mathematics

 

Courses Taught: Pre-Calculus, Calculus I, II, III, Linear Algebra, Numerical Analysis (undergraduate & graduate), Differential Equations.

 

Research work: My teamwork with Roger Temam solved an open problem of ten years for the SKT equations in biology.

 

2019 – 2020: University of California – Davis, California:  Pre-Six Lecturer

2015 – 2019: The University of Texas at San Antonio, Texas:  Assistant Professor

2013 – 2014: Indiana University – Bloomington, Indiana: Visiting Assistant Professor

2009 – 2013: Butler University – Indianapolis, Indiana: Mathematics Instructor

2007 – 2009: Colorado State University – Fort Collins, Colorado: Postdoctoral Fellow