Arpita Perugu Email & Phone Number | I am a Graduate Student at University of South Florida pursuing my Master's in Business Analytics and Information Systems. Gained work experience at Deloitte as a Business Technology Analyst. My skillset consists of Programming Languages: Python, Java, R, SQL, C# Python Packages: Pandas, Numpy, Scikit Learn Databases: Oracle, MySQL, MSSQL Server Machine Learning: Supervised and Unsupervised Learning, Linear and Logistic Regression, and algorithms (Decision Trees, Ensemble models, Neural Network, Deep Neural Network, RNN, CNN, SVM) Statistics: Descriptive and Inferential statistical methods, Hypothesis Testing, Z-Test, T-Test, Time- Series Models. Visualization: Tableau, Power BI Tools: RStudio, Azure ML, Jupyter notebook, Visual Studio, Microsoft Visio, UML, Jira, Anaconda, Git, MS Office, MS Excel, Eclipse

Arpita Perugu

I am a Graduate Student at University of South Florida pursuing my Master's in Business Analytics an...
Austin, Texas, United States

*50 free lookup(s) per month.

Arpita Perugu’s Email aperugu@amazon.com

Arpita Perugu’s Phone Numbers

Get ARPITA’s Phone Number (For Free)

Social Media

Arpita Perugu’s Location Austin, Texas, United States

Arpita Perugu’s Current Industry Amazon

Arpita Perugu’s Prior Industry University Of South Florida | Deloitte

Find accurate emails & phone numbers for over 700M professionals.

Software Development Engineer

2022-02-01 00:00:00 - Present

Graduate Teaching Assistant

2021-07-01 00:00:00 - 2021-12-01 00:00:00

Software Engineer

2018-01-01 00:00:00 - 2019-11-01 00:00:00

No Skills Available

No Languages Available

Arpita Perugu is a I am a Graduate Student at University of South Florida pursuing my Master's in Business Analytics and Information Systems. Gained work experience at Deloitte as a Business Technology Analyst. My skillset consists of Programming Languages: Python, Java, R, SQL, C# Python Packages: Pandas, Numpy, Scikit Learn Databases: Oracle, MySQL, MSSQL Server Machine Learning: Supervised and Unsupervised Learning, Linear and Logistic Regression, and algorithms (Decision Trees, Ensemble models, Neural Network, Deep Neural Network, RNN, CNN, SVM) Statistics: Descriptive and Inferential statistical methods, Hypothesis Testing, Z-Test, T-Test, Time- Series Models. Visualization: Tableau, Power BI Tools: RStudio, Azure ML, Jupyter notebook, Visual Studio, Microsoft Visio, UML, Jira, Anaconda, Git, MS Office, MS Excel, Eclipse