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Data Analyst

Location:
Ellicott City, MD, 21042
Posted:
February 01, 2017

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Resume:

Ted Tae Hwang

***** ******* ****** **. ******** City, MD 21042 443-***-**** ********@*****.***

EDUCATION

University of Maryland – College Park College Park, MD A. James Clark School of Engineering May 2013

Bachelor of Science in Electrical Engineering

Relevant College Courses: Linear Algebra, Engineering Probability, Discrete Mathematics, Calculus and C Programming PYTHON EXPERIENCE

Student (1 module) December 2016 – Present

www.Coursera.com

Read in 10 excel, .csv and .txt files into pandas dataframes. Then, set the index using an existing column rather than by order

Found specific indexes to Boolean mask in a dataframe by using a combination of control flow and conditional statements

Created datasets by appending, concatenating and merging data structures such as lists, series, dictionaries and dataframes

Retrieved quarterly averages by resampling datetime variable; year and quarter from the resample became new column name

Passed in two dataframes into a t-test function, from the scipy library, to see if two distributions were statistically different R EXPERIENCE

Personal Projects August 2016 – November 2016

Created a script that generated a list of URLs that holds web addresses where statistics on NFL players can be found

Obtained an R dataframe filled with statistics on NFL players by using control flow statements to web scrape data from the list of URLs into an array of list data structures. These lists were binded by row and then converted into the R dataframe.

Cleaned up the names of the NFL players using the grep function along with regular expressions and metacharacters

Calculated the mean, standard deviation, minimum and maximum of a metric for every row in the R dataframe

Transformed the R dataframe from a long-format to a wide-format using the dcast function found in the Reshape2 library

Visualized a metric for every individual NFL player by capitalizing on the facet_wrap feature found in the ggplot2 library

Determined the number of resources needed after 5 P.M. by manipulating POSIXlt variables and writing queries with sqldf

Found information through sapply functions which subsets dataframes by a category then applies custom functions to them Link to portfolio: www.rpubs.com/tae21042

Student (9 modules) March 2016 – September 2016

www.Coursera.com

Checked variables for skewness and applied methods, like standardizing and log transformations, to normalize them

Performed principal component analysis to create a new dataset with components that could explain 90% of the variance

Trained a random forest model to a training dataset and found the accuracy of the model to be 99% on the testing set

Analyzed the accuracy of general linear models, random forest models and boosting models through a confusion matrix

Created a multivariate regression model using the “mtcars” dataset in R to explore how a set of variables affects the output, miles per gallon. P-values, R-squared values and variance inflation factors were the tools used to create the best fit

Performed nested likelihood ratio tests to generate p-values that determine which variables are needed in a regression model

Plotted 30 bar graphs, histograms and line graphs for exploratory analysis. 5 graphs dealt with date and time variables 2

SQL EXPERIENCE

Student (1 module) June 2016 – July 2016

www.Coursera.com

Used select, from, where, group by, order by and having clauses to subset dataset in order to discover business intelligences

Used SQL subqueries to find how many NFL players had higher metrics than the average metric of an individual player

Determined the average profit per day of a department store through SQL joins; a relational schema was used as a guide PROFESSIONAL EXPERIENCE

Antenna Research Associates – Electrical Engineer April 2015 – February 2016 Beltsville, MD

Constructed an antenna prototype that met the gain specification in a new frequency band by meticulously modifying the dimensions of an older antenna one small increment at a time and then observing the outcome

Created a presentation to a customer on the measured data of 13 different antennas by transferring data from the measuring software to Excel. From Excel, line graphs were generated which was then pasted into Power Point slides

Communicated what management needed to be made to machine shop workers with very simple step-by-step instructions MasTec - Associate RF Engineer November 2013 - November 2014 Columbia, MD

Collaborated with a senior engineer to commission 10 distributed antenna systems using RF measuring instruments

Obtained 2 points of contacts for potential contracts by attending 1 AT&T convention and advertising MasTec’s services SKILLS: R, MySQL, Python, Tableau, Excel, Power Point, Regression Models, Machine Learning Algorithms, Git Hub and C



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