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Updated 3 years ago

Summary

Data Science student looking for internship or full-time opportunities. Projects include Natural Language Processing, price prediction, classification, and exploratory data analysis. Prior to Metis, I worked in account management in the corporate insurance industry.

Skills

  • Python
  • SQL

Education

August 2011 May 2015

BA - Economics at University of California, Berkeley

Experience

January 2018 April 2018

Data Scientist at Metis

Part of a selective 12-week immersive data science program. Developed several data science projects using statistical modeling, machine learning, programming, communication, and design. Projects include:

• Topic Modeling on Travel Destinations – Scraped travel information from Fodor’s Travel Guide and used Natural Language Processing techniques to categorize travel expert-recommended activities across the United States. The techniques used included Latent Dirichlet Allocation, Latent Semantic Analysis, and Non-Negative Matrix Factorization. The resulting visualization was created on Tableau.
• Topic Modeling On Disneyland Trip Reviews – Applied Natural Language Processing algorithms to identify common topics among Disneyland and Disney California Adventure reviews on TripAdvisor. The techniques used included Latent Dirichlet Allocation, Latent Semantic Analysis, and Non-Negative Matrix Factorization.
• Loan Default Prediction – Used classification models to predict if a loan would default on the Lending Club platform. The classification methods used included Logistic Regression, Decision Trees, Random Forest, K Nearest Neighbors, and Gaussian Naive Bayes.
• Predicting Timeshare Resale Values in Hawaii – Used data scraped from My Resort Network and TripAdvisor and created Linear Regression and Polynomial Regression models to predict timeshare resale values in Hawaii.
• Analyzing Foot Traffic on NYC’s MTA System – Identified the New York City borough with the highest unregistered voter count, which was Queens. After cleaning and analyzing MTA data from the New York City Data Portal, computed total foot traffic for each MTA station within Queens in regards to time of day, day of the week, and calendar day in 2017.

August 2015 January 2018

Account Representative at Woodruff-Sawyer & Co.

Woodruff-Sawyer is one of the largest independent insurance brokerage firms in the nation. For nearly 100 years, we’ve been partnering with clients to deliver effective insurance, employee benefits and risk management solutions, both nationally and abroad. Headquartered in San Francisco, Woodruff-Sawyer has offices throughout California and in Oregon, Washington, Colorado, Hawaii and New England.

• Provided guidance and expertise on corporate insurance policies to technology, financial institution, and life science companies
• Analyzed the sufficiency of prospective clients’ insurance policies, making recommendations based on clients’ growth and industry trends
• Monitored 200+ policies of companies with demonstrated ability to meet multiple deadlines in a fast-paced setting
• Constructed insurance programs for individual companies based on in-depth analyses of the clients’ operations and contractual obligations
• Created client deliverables, such as proposals, summaries of insurance, rate comparisons, coverage charts, presentation materials, marketing reports, etc.
• Served as a liaison between insurance carriers and clients, ensuring all necessary documents are submitted, contract requirements are fulfilled, and inquiries are handled in a timely matter
• Evaluated and solved billing discrepancies, analyzing company databases
• Discussed complex insurance components to audiences of various positions and varying knowledge of insurance