Resume


Erin T. Werner

EDUCATION

University of California, Berkeley, CA - Jan 2020 – May 2022

  • M.Sc. in Information & Data Science - GPA: 3.77

University of California, San Diego, CA - Sep 2015 – Jun 2019

  • B.S. in Applied Mathematics & Minor in Computer Science; College Honors – GPA: 3.58


WORK & RESEARCH EXPERIENCE

Software Engineer – Goldman Sachs, New York NY/Remote - 2022 – Present

  • Developed custom internal tools in Java to support private wealth management teams
  • Coordinated data filtering techniques across platforms, at scale
  • Strategized design and implementation for user optimization

Software Engineer – eQ Technologic, Costa Mesa CA/Remote - 2019 – 2022

  • Created custom software solutions in Java to assist clients with their data management
  • Designed analytic reports, utilizing SQL and BI, to provide insight on data migrations
  • Consulted with clients about their data needs and implemented the solutions

Nuclear Data Analyst – Lawrence Livermore National Laboratory, Livermore CA - 2018

  • Queried SQL databases to form data feature vectors that would then build a classifier
  • Implemented ML techniques in Python to improve nuclear detection at U.S. borders
  • Presented at the Am. Nuclear Conference as a Dep. of Homeland Security representative

Programing Assistant – Center for Peace & Security Studies, San Diego CA - 2017 – 2019

  • Wrote software programs in R to generate data visualizations that were informative
  • Collaborated with a team to construct a Web Scraping/SOAP Parsing tool in R
  • Assisted in data wrangling, data pre-processing, and data mining


PROJECTS

NFT Price Prediction - 2022

  • Built an ARIMA model to predict the price of an NFT with 84% precision

Tweet NLP Sentiment Analysis - 2021

  • Applied BERT Language Modeling to determine the emotion of text data with 92% accuracy

Food Recommendation System - 2020

  • Constructed Collaborative Filtering model with Pearson similarity correlation
  • Compared to Latent Factorization approach with Singular Value Decomposition

MNIST Digit Classifier - 2019

  • Built 4-layer Convolutional Neural Network in PyTorch
  • Achieved 96% accuracy with Stochastic Gradient Descent approach

March Madness Outcome Prediction - 2019

  • Applied Logistic Regression to determine potential results from tournament

Unsupervised Vehicle Classifier - 2018

  • Developed custom algorithms to transform data into suitable feature vectors
  • Optimized K-Means algorithm to build a representative vehicle classifier