Data Analyst

VIDHYUT PRAJAPATI

BOSTON, MA ***** *********.*@*****.***.*** +1-857-***-****

EDUCATION

Northeastern University, Boston, MA January 2018-December 2019 Master of Science in Engineering Management: Concentrating in Analytics Related Courses: Data Mining Engineering, Database Management and Database Design, Deterministic Operation Research, Probability and Statistics, Economic Project Management, Economic Decision Making Gujarat Technological University, Gujarat, India July 2013-May 2017 Bachelor of Engineering in Electronics & Telecommunications TECHNICAL SKILLS

Programming Languages: R, Python, SQL, UML, Basics of C, C++ Data Visualization Tools: Tableau, R Studio, MATLAB, Microsoft Excel, PowerPoint Database: MySQL, Microsoft SQL Server, PostgreSQL, DB2, MS Access Statistics: Descriptive statistics, Hypothesis testing, Linear regression, Decision Trees, KNN Functional skills: Data Modelling, Data Warehousing, Data Migration, Data Mining, Statistical Analysis, ETL, Predictive Analysis, Machine Learning

PROFESSIONAL EXPERIENCE

Data Analyst Param Agro-Industries, Gujarat, India (MySQL, Python) January 2017-November 2017

• Migrated data into the cloud from Microsoft SQL Server, SAS and PostgreSQL by scripting in Python to reach conclusions for managerial actions and strategies, thus increasing the efficiency by 35%

• Presented findings and data to the assistant analytical team to improve strategies and operations; performed a market analysis to efficiently achieve objectives including demographic data cluster and operations flow

• Dispensed ad-hoc analytic support to solve Supply Chain, Logistics & Quality issues experienced during deployment on site; proposed solutions to improve system efficiencies and reduce total expenses Data Analyst Intern Akaaish Mechatronics Limited, Gujarat, India (R:stats, T-SQL ) June 2016

• Analyzed and tracked data of 400 company workers in 4 production units; performed ETL to optimize the performance of queries and stored procedures with modification in T-SQL statements and designed ad-hoc reports (SSRS), provided insights & strategies, achieving an increase of 15% in result

• Tracked and monitored client payment processes weekly; studied inventory usage and transactions

• Conducted in the newly formed method of new account information input; saved approximately 200 man-hours annually

ACADEMIC PROJECTS

Automated Cooking System (MySQL, StarUML), Northeastern University September 2018- December 2018

• Created Database on MySQL workbench for each process of cooking adopting SQL Server queries and Subqueries

• Designed Use Case Diagram, Activity Diagram and Sequence Diagram Using StarUML to reduce the complexity and to understand the flow of processes; Prompted ERD consisting of 22 tables to scale the better flow of the model

• Fixed Stored procedures, Triggers, and Privileges for better security, to improve the performance of the data model Boston Housing Market Prediction (R: stats, Excel), Northeastern University May 2018-July 2018

• Executed data pre-processing (cleaning, integration, transformation, and reduction) of different areas of Boston city to evaluate predictive performance using R packages: dplyr, tidyr, string

• Analyzed the data (EDA) and implemented XGBoost package for identifying correlation and significant variables

• Developed a linear model and predicted the Boston housing market thereby giving insights to the investors Analysis of Hillary Clinton E-mails (Python), Northeastern University August 2018-September 2018

• Accomplished scraping on Wall Street Journal article for anomaly detection adopting Python Libraries (Beautiful Soup and Urllib); executed data wrangling and transformation using” Pandas Library” in Python

• Applied “Collections Library” to count the top most common Email-ID based on the undertaken attributes IoT based Air pollution detection system(Python), Gujarat technological University, Gujarat, India April 2017

• Designed a module that consisted of different air detection sensors, which accurately measured the gas contents and account through Wi-fi; Collected data in a cloud through Raspberry pi 3 and built a mobile application, through which users could access an accurate and real-time data easily; GPS module gave an exact location

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