Data Scientist / Data Analyst

GANDHAR KOTHARI

857-***-**** *******.*@*****.***.*** www.linkedin.com/in/gadharkotharineugrad

Education

Northeastern University, Boston, MA

Master of Science in Engineering Management (specializing in Data Analytics) Dec 2017 Coursework: Probability and Statistics, Data Mining, Machine Learning, Database Design, Business Intelligence Collect Store and Retrieve Data, Economic Decision Making, Marketing Analytics, Operations Research Shivaji University, Kolhapur, India

Bachelor of Engineering in Electronics June 2012

Technical Skills

• Languages: R, Python, SQL

• Tools: R studio, Jupyter, Numpy, Pandas, Scikit-learn, Matlab, XLminer

• Databases: MSSQL, MySQL, Postgresql, Oracle, NoSQL (MongoDB)

• ETL and BI: Toad data modeler, SSIS, SSRS, SSAS, Visual Studio, Talend, Tableau, Qlik, PowerBI, R shiny

• Data Analysis: Statistical and Predictive Modelling, Time Series, Hypothesis and A/B Testing, Web scraping

• ML Algorithms: Regression, Decision Trees, Random Forest, Bagging, Boosting, Naïve Bayes, Knn, Neural Networks

• Big Data: Hadoop, Apache Spark

Professional Experience

Data Analytics Teaching Assistant at Level Education, Northeastern University Aug 2017-Dec 2017

• Trained professionals to perform statistical data analysis on real world datasets using tools like R, SQL, Excel and Tableau.

• Assisted students to understand concepts of statistics, data mining and data visualization and helping them to resolve problems in their capstone projects.

Data Scientist Co-op at Door of Clubs, Boston, MA (Rapidly growing start-up) May 2017-Aug 2017

• Built supervised predictive model in R and Python to predict categories of new registered club based on historical data.

• Performed data cleaning and conducted data exploratory analysis on word count of company applications to recommend the length of their applications subject and description.

• Analyzed and visualized large dataset of student profiles through MySQL and R to provide useful information and insights to management of Door of Clubs.

• Developed algorithm to anticipate which criteria used by companies have highest success ratio for students.

• Implemented descriptive analysis on student’s applications data and improved success ratio by 20% by recommending companies the best suitable time to post applications on Door of Clubs platform.

• Generated dashboards for business users to take data driven decisions using Tableau and Qlik. Associate Engineer at Qlogic Private Limited, India (Leading provider of Data center networking solutions) Aug 2013- Dec 2015

• Conducted functional testing of device drivers and Qlogic management application as a part of product release.

• Prepared, executed test case plans for features of Qlogic products. Recommended features for product improvement.

• Performed Sanity, black box and regression tests for network and storage features of Qlogic adapters.

• Improved testing efficiency up to 20% by implementing software testing methodology.

• Analyzed critical and blocking issues to ensure best quality of product and interacted with customers to solve them. Projects

Forecasting of Bowling Price and Revenue using Time Series Oct 2017

• Applied time series models VAR and ARIMA to forecast price and revenue of bowling and shoes rental for next 365 days.

• Plotted graphs to check seasonality, trend and stationarity of the data. Derived ARIMA components using ACF,PACF plots

• Computed and compared accuracy values of both models. Selected best model (VAR) with RMSE value of 0.6 %. Loan Defaulter Classification using Logistic Regression: May 2017

• Explored and cleaned credit data set and applied logistic regression model to predict probability of loan defaulter.

• Improved classification of defaulter by plotting ROC curve and selecting appropriate threshold value.

• Compared different logistic regression models using area under curve and calculated accuracy by confusion matrix. Data integration and Data modelling of AdventureWorks Data warehouse: Mar 2017

• Designed dimensional model for retail and inventory data warehouse to perform reporting.

• Integrated data from four different DBs to MySQL using Talend and SSIS and performed ETL operations on 4.6M records

• Created dashboards using Tableau, Qlikview to answer business questions related to purchasing, sales and profit/loss etc. Prediction of house prices using Regression and Boosting in Python: Feb 2017

• Explored and visualized housing data using seaborn and other plots to check important factors that affect house prices.

• Built regression model on data to predict house prices, implemented GBM to improve accuracy of prediction up to 91.5%. Price prediction of Toyota Corolla using Decision Tree and RF: Nov 2016

• Prepared, cleaned and partitioned dataset for analysis and prediction. Created dummy variables for categorical predictors

• Built regression tree on dataset and employed random forest method to predict prices of used cars based on specifications

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