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Data Analyst

College Park, Maryland, United States
May 01, 2019

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Prince Frederick, MD *****



University of Maryland, College Park, MD

Bachelor of Science, Expected: May 2019

Major: Information Science, Cumulative GPA: 3.67/4.0, Major GPA: 3.93/4.0 Semester Academic Honors (3 Semesters), Recipient of OMSE Academic Excellence Award (2018 & 2019), Relevant Coursework: Data Science Technique, Data Sources and Manipulation, Data Analytics for Professionals, Intro to Data Visualization, Database Design and Modeling College of Southern Maryland, Prince Frederick, MD Associates Degree, Graduated: December 2016

Major: Business Administration, Cumulative GPA: 3.783/4.0 Recipient of Faculty Scholarship Award (2016)


Data Science Technique

§ Extracted and collected real-world datasets from variety of data types and formats

§ Determined a proper filing system to organize and store the datasets for easier collaboration

§ Cleaned, standardized, and normalized the data to prepare for data analysis

§ Designed predictive model with the cleaned dataset to categorize attributes and created visualizations

§ Interpreted and presented the results to derive a productive conclusion Data Source and Manipulation


Tech and Research Workshop, Univeristy of Maryland, November 2018

§ Explored deep learning frame work to power autonomous driving via images from single front-facing camera; Created a virtual environment using Unity & collected training data to train deep neural network

§ Used the trained network to steer a vehicle on both training and testing data and attempted to model a system for safer navigation for autonomous vehicles or driver-less car TECHNICAL & LANGUAGE SKILLS

§ Research: Data Science Research Methods, Survey Creation, Data Mining

§ Data Analysis Tools: OpenRefine, Weka, Gephi, Tableau, R

§ Programming Language: R, Python, JavaScript, MySQL, HTML, CSS

§ Database Management: Database Design and Management, Data Analysis, Visualization of Data

§ Collected large datasets through scalable, automated means such as scrapers

§ Utilized Python in Pandas to convert data into actionable insights by

§ Transformed data among a variety of formats and standards

§ Prepared the data for analysis using open source software library such as Pandas, Numpy Data Visualization

§ Utilized Tableau, and other dashboard/visualization tool sets for data intelligence and analysis

§ Applied existing techniques from scalar, volume, multidimensional, textual, graph-based, tree-based, and temporal visualization to actual problems and data

§ Used existing visualization tools and techniques to analyze basic datasets Fake News vs. Satire: A Dataset and Analysis, University of Maryland, September 2017– April 2018

§ Collected articles of fake news from diverse websites, verified with rebutting articles, hand-coded major themes of the articles and helped in its dataset creation

§ Coauthor of the published research project with Dr. Jen Golbeck to identify, study, and characterize fake news

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