RISHABH BADJATYA

+1-201-****-***-** Perrine Avenue, Jersey City, NJ www.linkedin.com/in/rishabhbadjatya adjrx6@r.postjobfree.com github: rishbadj EDUCATION

Master of Science in Data Science New York Institute of Technology (New York, USA) Expected Jun 2021 Relevant Courses: Programming for Data Science, Big Data, Database Management, Machine Learning, Data Visualization, Data Mining, Operation Research, Probability and Stochastic Processes, Theory of Computation and Compilation Bachelor of Science IES IPS Academy (Indore, India) Aug 2015 – Jul 2019 Relevant Courses: Computer programming, MATLAB, Signal Processing, Cyber Security, IOT, Computer Systems, VLSI TECHNICAL SKILLS

Programming Languages: Python, R

Database: MySQL, SQL Server, MS-Access, SSIS, Mongo DB Reporting and Analytics: Tableau, PowerBI, MS-Excel, Google Analytics, Spreadsheets, JIRA Certifications: Data Analyst Python, Data Analyst SQL Server, Fundamentals of Tableau (DataCamp), Tableau 2020 A-Z(Udemy) WORK EXPERIENCE

Data Analyst INTERN WEBCRAFT IT (Indore, India) May 2020-Aug 2020

Implemented ETL (Extract Transform and Load) strategies for processing Customer Data on various Warehousing Projects

Executed SAP HANA to transform all Critical Enterprise Functions from Finance to Supply Chain to Customer Service and Marketing

Applied Data Collection Methodologies, Technologies Using SQL and Python projects in Warehousing, Supply Chain and Finance PROJECTS

Naïve Bees: Deep Learning with Images New York Institute of Technology Sep 2019-Nov 2019

Build a deep learning model that can automatically detect honeybees and bumble bees in images

Applied sklearn's StandardScaler function to scale our data so that it has a mean of 0 and standard deviation of 1

Enforced Convolutional Neural networks (CNN) for image classification with sequential model and achieved an 0.99 AUC (out of 1.00)

Language: Python, IDE: Jupyter Notebook, Libraries: Pillow, keras, scikit-learn, scikit-image, and NumPy Reducing Traffic Mortality in the USA New York Institute of Technology Jan 2020-Mar 2020

Utilized Unsupervised learning to determine traffic related-fatalities using algorithms such as K-Means Clustering, Linear Regression

Established a multivariate linear regression model using the fatal accident rate as the outcome

Performed a principal component analysis (PCA) on the standardized data and boosted the accuracy to 78%

Visualized the distribution of speeding, alcohol influence and percentage of first-time accidents in a direct comparison of the clusters

Language: Python, IDE: Jupyter Notebook, Libraries: Pandas, Seaborn, matplotlib, scikit-learn, NumPy Give Life: Predict Blood Donations New York Institute of Technology Jan 2020-Mar 2020

Designed a binary classifier to predict if a blood donor is likely to donate again

Explored automatic model selection using TPOT and AUC score that we got was 0.7850

Operated log normalization on our training data and improved the AUC score by 0.5%

Used logistic regression to implement binary class prediction

Language: Python, IDE: Jupyter Notebook, Libraries: Pandas, TPOT, scikit-learn, NumPy Analyze International Debt Statistics May 2020-Aug 2020

Analyzed International debt data collected by the World Bank and which country owns the maximum amount of debt

Gathered the total and average amount of debt that is owed by the countries across different debt indicators

Found the country with the highest amount of principal repayments

Database: MYSQL

Visualizing the Fight Against COVID-19 Sep 2020-Dec 2020

Created Tableau scorecards, dashboards using stack bars, bar graphs, scattered plots, geographical maps, gantt charts by using show me Functionality

Developed rich interactive graphics and synchronize data visualizations of large, structured data in user-friendly formats

Eliminating the hard-coding and manual sorts by using a level of detail calculated field and obtaining 70% better results

Tool: Tableau

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