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Work Experience
Data Science Intern
Tishman Speyer•  September 2019 - December 2019
• Built predictive models to predict client lease renewals (churn) • Created target variable based upon client requirements • Assisted in cleaning data and engineering features • Built neural network to create entity embeddings for categorical variables • Performed dimension reduction techniques such as principal component analysis • Built Google web crawlers to extract client stock exchange data and company size
Software Programming Intern
NYU Public Safety Lab•  May 2019 - September 2019
• Built scraper classes to collect jail roster data from across the country • Helped build python object-oriented framework for writing generalized scrapers • Pioneered methodology using Tabula for scraping jail roster data from pdfs • Trained team members and created documentation on pdf scraping methodology
Configuration Specialist
Axiom Software Laboratories•  September 2015 - June 2018
• Worked with Oracle relational databases and used SQL on a day-to-day basis • Integrated various sources of client financial data, built customized pipelines for financial data flow in an agile environment, and troubleshooted data discrepancies • Conducted demo walkthroughs of customized data pipeline configurations for clients • Effectively communicated with the client to understand their technical requirements and resolve their inquiries • Clients: Morgan Stanley, PNC Bank, Bank of America
Education
New York University (NYU), New York
Data Science, MS•  September 2018 - May 2020
Courses: - Machine Learning Theory - Deep Learning Theory - Text as Data - Responsible Data Science - Computational Linear Algebra & Optimization - Probability & Statistics - Advanced Python Programming - Big Data - Time Series Forecasting
Hofstra University
Business Management, BA•  September 2011 - May 2015
Minor in Computer Science - Course Work included: Object-oriented programming, Data Structures, and Dynamic Programming, Run-Time Complexity Theory - Languages: Python, C++, Java
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