Data Python

DIVESH NARESH GUPTA

*************@*****.*** Worcester, MA 774-***-**** LinkedIn

EDUCATION

Clark University Worcester, MA Aug 2019 – Dec 2020 Master of Science in Information Technology GPA: 3.8/4.0 Coursework: Business Intelligence, Information System Analysis & Design, Data Mining with Splunk, Agile Software Development Methodology, Cyber Security Warfare & Risk Management Thakur College of Engineering and Technology, University of Mumbai Mumbai, India Aug 2016 – May 2019 Bachelor of Engineering in Electronics and Telecommunication Paper Publication: Human Disease Detection Using Data Mining, Team Project (ISSN- 2349-5162) - Jetir TECHNICAL SKILLS & CERTIFICATES

Certifications: IBM-Data Science, Salesforce Admin, Lean Six Sigma (Green Belt) Six Sigma Global Institute

Programming Language & Databases: Python (NumPy, pandas, seaborn), R, MATLAB, SQL, MySQL, Azure Data Analysis, Visualization & Tools: Tableau, Power BI, Looker, Microsoft Excel (Macros, Pivot-tables), MS Office Competencies: BI Dashboards, AI, TCP/IP, Networking Architecture PROFESSIONAL EXPERIENCE

Graduate Teaching Assistant – Business Intelligence, Clark University, Worcester August 2020 – Dec 2020

Spearheaded a batch of 25 students individually to get hands-on experience with the basics of Power BI and Tableau

Assisted with assignments, journal, exercises, and conduct class every week

Recommended corrective actions to the professor by supervising activities in the classroom to emphasize systematic procedures

Intern, Pushpam Computers & Software Pvt. Ltd, India April 2018 – Nov 2018

Successfully presented market trends through interactive dashboards using Tableau story dashboards

Analyzed historical reports, market and industry trends, service performance indicators, and service loopholes to be able to propose and recommend solutions and remedies appropriately

Contributed to multiple projects by solving complex problems in a highly cross-functional environment PLC Automation Intern, Siemens, India May 2015 – June 2015

Operated with engineers from the automation department to examine various automation tools such as CNC machine and PLC

Design tools used in industry and kept records in Excel

Designed Ladder Diagram, Structured Text, Function Block Diagram, Process Maps, Instruction List, Sequential Function Charts and review and analyze gaps for Manufacturing equipment. PROJECT EXPERIENCE

Capstone Practicum Research on Cloud Computing Python, AWS May 2020 – Aug 2020

Identified utilization of cloud computing systems as AWS Commerce platform which includes enabling developers and software companies to easily distribute, and make money from their cloud-based products

Enabling consumers of cloud-based software to evaluate, buy, and 1-click deploy even the most complicated cloud architectures

Leverages recognized domain expertise, business acumen, and experience to influence decisions of executive business leadership, development partners, and industry standards, groups Tour de France Tableau, Advance Excel, SQL Jan 2020 – Apr 2020

Instrumented formulas and generated sets for statistics on attendance, such as the number of wins, state participation, and records by creating visualizations in Tableau

Formulated logistic regression and random forests in R studio to predict the results

Tabulated the statistics in Excel by different stages to display the winner's records in different categories via dashboards Human Disease Detection Python, MS Excel Aug 2018 – May 2019

Analyzed data and built a predictive model using logistic regression in Python to identify borrowers with a high-risk score, reducing risk by 5% researched analysis based on healthcare predictions using data mining to reduce the medical cost by 30%

Engineered various methods of data mining for chronic kidney disease prediction using clinical details and choose the most accurate method of prediction for user interface by importing medical data

The result which is approximately 95%-99% accurate based on various models which were neural network, support vector machine, and random forest data-mining techniques have proved successful in predicting and performing diagnosis of various diseases

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