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Data Analyst

Location:
Somerset, NJ
Posted:
November 16, 2020

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Resume:

Daksh Parekh

New Brunswick, New Jersey ***** 201-***-**** adhv1k@r.postjobfree.com

LinkedIn: www.linkedin.com/in/dakshparekh

EDUCATION

Rutgers University Rutgers Business School, New Brunswick, NJ September 2019 - December 2020 Master’s in Information Technology and Analytics GPA: 3.6/4.00 NMIMS University MPSTME, Mumbai, India June 2015 – May 2019 B. Tech in Information Technology GPA:3.00/4.00

RELEVANT COURSEWORK

Information Security, Business Analytics Programming, Analytics for Business Intelligence, Operations Analysis, Supply Chain Management Strategy, Project Management.

SKILLS AND CERTIFICATIONS

Programming Languages: Python, R, C++, Java, HTML, CSS Database Management: SQL, Oracle DB, AWS RDS, MS Excel (V-lookup, VBA, Pivot Tables, Macros, Data Analysis Tool) Tools & Software: Tableau, Base SAS, SAS Visual Analytics, SQL, MATLAB, Rstudio, Xcode, Android Studios Operating Systems: Windows, Linux Ubuntu, Raspbian OS, Mac Certifications: Tableau 2020:Certified Assosiate, Google Analytics, Programming in Java. EXPERIENCE

Remote Intern – Thaumaturgix, New York July 2018 – August 2018

• Studied and analyzed various stages of the lifecycle of a real-world mobile application.

• Developed iOS Mobile Application using Xcode, implemented Augmented Reality (AR) Technology using ARKit.

• Created an application that allows the user to record a short video and generated a printable thumbnail image from the video.

• The engineered thumbnail then upon scanning, the application identifies the dimension of the image.

• Programmed application will overlay an augmented reality screen on the identified dimension of the thumbnail.

• Recorded video is fetched from the cloud and then overlayed using ARKit on the identified dimensions of the image. Data Analyst Intern – Magnamious System Pvt. Ltd., Mumbai, India May 2018 – June 2018

• Analyzed complex data sets using Python to gauge the revenue potential by identifying the best practices in process improvement and business intelligence.

• Built, implemented and reiterated predictive models using algorithms like logistic regression and decision tree.

• Wrote python script to analyze the data and generate invoices, reducing man-hours by 95%

• Developed a generic utility for conversion of data from Excel sheets into CSV and JSON formats.

• Implemented the system using client-server architecture in Python. Web Developer Intern – IUS Equipments Pvt. Ltd., Navi Mumbai, India June 2017 – July 2017

• Worked with their web development team to develop the company’s webpage.

• Performed database connectivity, wherein passwords get stored in an encrypted manner.

• Initiated an autogenerated notification using PHP using Codeigniter. PROJECTS

Government Responses to COVID-19 March 2020 – May 2020

• Dataset: Coronavirus Government reponse tracker by University of Oxford.

• Studied the responses and actions taken by the governments of top 10 affected countries to deal with the pandemic.

• Converted qualitative data to quantitative data which was used to derive statistical information in MS Excel.

• Created a variable that could factor other variables to understand which country dealt with the situation appropriately.

• Visually represented 3 dashboards using Tableau describing Government Actions, Investments, and Responses.

• Designed a ranking system to conclude which country was able to respond to the pandemic most effectively. Airline Performance Analysis September 2019 – November 2019

• Perform analysis on data of various airlines by factoring different variables and using statistical analysis.

• Applied ETL on the data used regression to analyze data using R.

• Built trend cycle, seasonality, and time series plots to better understand the trends using R.

• Forecasted the data using mean, naïve, seasonal, and ARIMA modeling using R.

• Visually represented the data using Tableau to create interactive dashboards.

• Recorded the observations to build a ranking matrix to determine the best airline based on our factors and derived further relationships between airlines and their hubs.



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