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Python, R, SQL, Tableau, PowerBI, Programming, Mathematics, Statistics

Location:
Boston, MA
Posted:
April 30, 2020

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Resume:

JAY BHESANIA

Boston, MA ***** 657-***-**** adc06g@r.postjobfree.com https://www.linkedin.com/in/jaybhesania EDUCATION

Northeastern University, Boston, MA May 2020

Master of Science in Industrial Engineering: Concentration-Analytics Related Courses: Computation & Visualization, Data Mining in Engineering, Data Warehousing and Business Intelligence, Data Management and Database Design, Probability and Statistics, Project Management Mumbai University, Mumbai, India May 2018

Bachelor of Engineering in Mechanical Engineering

SKILLS

Programming Languages: Python 3.0, R, SQL

Databases: MySQL, PostgreSQL, MSSQL, Oracle SQL, MongoDB Data Analytics and Visualization: Excel, Tableau, Power BI, Alteryx, Talend Libraries: NumPy, Pandas, Seaborn, Matplotlib, Pyplot, Scikit learn, ggplot2 Tools and IDEs: PyCharm, Flourish, Datawrapper, R Shiny, Jupyter Notebook, ER/Studio, Github PROFESSIONAL EXPERIENCE

SQL developer Intern KAMP Infotech, Maharashtra, India Dec 17-May 18

• Migrated legacy SQL query using Stored Procedures, triggers and functions in MySQL improving performance by 20%.

• Honed analytical skills in python for efficient system operations and reduced overall time for consultation by 15%.

• Generated Ad hoc queries and reports in tableau for evaluating KPI and leading strategic initiatives.

• Co-operated business meeting to understand client requirements and improvise the marketing strategy. Engineering Intern Uran Gas Turbine Power Plant, Maharashtra, India Dec 16-Feb 17

• Learned about the functioning of a gas turbine power plant as well as waste heat treatment system.

• Analysed logistic process with clients and contribution of the individual department for continuous efficiency of the process.

• Brainstormed alternative ideas for heat treatment and applied it in a pragmatic situation for minimal loss of heat. ACADEMIC EXPERIENCE

Boston housing (Python, Jupyter) Sep 19- Dec 19

• Performed data preprocessing for more than 500 instances and 14 features using Pandas as well as Numpy library.

• Tested various methods on model with R squared value between 59-95% using scikit-learn to find a good fit.

• Visualized data and found a correlation between variables for each tested model using matplotlib and seaborn. Airbnb pricing strategy, Northeastern University, MA (R) Sep 19- Dec 19

• Executed data preprocessing (Cleaning, integration, transformation, and reduction) of 6 major cities having 20+ features to evaluate predictive performance using packages: dplyr, tidyr, stringr.

• Examined data using Tidyverse package for correlation and significant variable from around 75000 data instances.

• Performed Statistical analysis on the rise of Airbnb over different city generating heatmap and visualized conclusion on a map using ggmap package.

School report Datawarehouse, Northeastern University, MA (Databases, Talend, Tableau, PowerBI) Sep 18- Dec 18

• Extracted and joined multiple databases like MySQL, MSSQL, Oracle, Postgres and spreadsheet files along with analyzing data and common fields.

• Integrated data from multiple databases into MySQL using Talend and cleaned it for further analysis on BI.

• Visualized complete integrated data from MYSQL and created Dashboard using Tableau and Power BI. Level Up Life, Northeastern University (MySQL) Jan 19- Apr 19

• Built a system that lets a user track their daily achievements while progressing in a video game-style online platform.

• Constructed a database using MySQL that mapped citizen’s behavior in the society and assigned points based on their activities that determined their standing in the society and enabled them for various benefits from the government.

• Implemented different triggers, procedures, and views for the same. Farmers Market Project (R) Jan 19- Feb 19

• Cleaned and Analyzed data for US Farmer's market containing over a million datapoint to detect the evolution of Famers Market.

• Implemented time series to identify the trend of the market over the years and mapped it using USMAP library along with ggplot2 to portray its evolution for non-profit use.



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