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Data Python

Dallas, TX
February 29, 2020

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Amit Mutgi

+1-475-***-****; ; ;

Dallas, Texas;!/ EDUCATION

The University of Texas at Dallas May 2020

M.S., Information Technology and Management (Dean’s Excellence Scholarship Award) Visvesvaraya Technological University Jul 2015

Bachelor of Engineering, Electronics & Communication TECHNICAL SKILLS & RELEVANT COURSEWORK

Languages: R, SQL, PLSQL, Java, Java Script, C, Python, VBA, Excel Macros ML Packages: Pandas, NumPy, Matplotlib, Seaborn, SciPy, Scikit-Learn, Keras, Tensorflow Tools: MS Excel, MySQL, Microsoft Access, Oracle, MATLAB, Tableau, Microsoft PowerBI, QlikView, Adobe Analytics, Google Analytics, GitHub, SAP HANA, SAP Business Objects, Lumira, SAP Crystal Reports, Microsoft Visual Studio Certifications: Udemy – Python for Data Science & Machine Learning; Data Science & Deep Learning with Python BUSINESS EXPERIENCE

National Healthcare Solutions Inc, Dallas, Texas Jun 2019 – Dec 2019 Business Systems Analyst Intern

• Performed descriptive and exploratory data analysis on claims and eligibility data using SQL, MS Excel and Python to generate reports based on the client’s requirement with a client satisfaction index of 97%

• Created executive summaries of various clients using interactive dashboards in PowerBI to analyze the operational performance and measure their monthly KPI’s

• Programmed VBA scripts to generate eligibility files that contains employee health insurance enrollment and maintenance data Oracle Financial Services Software Bangalore, India Mar 2016 – Jul 2018 Data Engineer

• Developed RTGS, ACH & Cross Border Payment modules of Oracle's FLEXCUBE Payments & designed appropriate fix for the issues raised using MySQL and Oracle SQL server

• Created and modified SQL queries to analyze the integrity of transactional data with the use of stored procedures, nested joins, custom views and ETL triggering a 15% increase in accuracy of payments related Adhoc reports ACADEMIC PROJECTS & COMPETITIONS

Web Scraping of US Census Data Apr 2019 – May 2019

• Used the BeautifulSoup Python library to extract unconventional census data for top 8 cities with the highest population in the United States from Wikipedia page

• Sequenced the dataset with each city’s supplemental data like Government and racial composition information from their respective Wikipedia sites and structured the dataset to be uploaded to BigQuery table for interactive analysis Informac, Data Science Challenge – Winner Mar 2019 – Apr 2019

• Predicted the health scores of restaurants in Los Angeles county dataset with over 200,000 records using random forest regression in Python with an accuracy of 94.32%

• Identified the key factors impacting the health scores of the restaurant using random forest classification and analyzed the relationship between health code violations and the scores using chi-squared test

• Visualized the patterns in terms of how health scores of restaurants change over time in PowerBI Movie Box Office Prediction Mar 2019 – Apr 2019

• Forecasted box office performance of movies for the year 2019 based on 20 years of historical data using Random Forest Regressor in Python with an accuracy of 86.3%

• Applied Naive Bayes Classifier to predict the sentiment based on movie review data with an accuracy of 92.5% LINKViz 1.0, Data Visualization Challenge – Finalist Feb 2019 – Mar 2019

• Inspected the production of vanilla to identify trends & relationship in the yield of vanilla with regional weather conditions and average price over a span of 56 years

• Created a deep dive model to allow new businesses and consumers to interact with Tableau dashboard and get insights on vanilla harvest, cultivation and revenue trends around the world LEADERSHIP & ORGANIZATIONS: Data Science Club, UTD – General Secretary

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