University of Massachusetts, Amherst
Master of Science in Statistics (3.98 GPA)
Aug. 2019 – May 2021

Coursework: Regression, Bayesian Statistics, Neural Networks, Machine Learning, Natural Language Processing (NLP), Categorical Data, Survival Analysis, Design of Experiments, Data Visualization

Vassar College
Bachelor of Arts in Chemistry, Minor in Computer Science (3.99 GPA)
Aug. 2006 – May 2010

General Honors, Departmental Honors, Phi Beta Kappa Society. Publications in ACS Omega, Biophysical Journal, and Limnology and Oceanography


The Travelers Companies
Consultant, Data Science Leadership Development Program
Jun. 2021 – Present
Data Science Intern
Jun. 2020 – Aug. 2020
  • Implemented a propensity model using XGboost to estimate the impact of a new insurance product on premiums
  • Wrote Python functions in support of an initiative to transition from SAS to Python
ROI Solutions
Database Developer II
Feb. 2018 – Jan. 2020
  • Improved the performance of a client’s direct mail campaign by developing a model in Python and DataRobot to identify likely responders, increasing the client’s campaign response rates by over 20%
  • Refactored and created new stored procedures in a CRM database to add functionality, improve performance (often by 2x or more), and improve code clarity and maintainability
  • Worked with client-facing teams to address issues, identify bugs, and better understand customers’ needs
The Cadmus Group
May 2016 – Feb. 2018
Senior Analyst
May 2014 – May 2016
May 2012 – May 2014
Research Analyst
Aug. 2011 – May 2012
  • Conducted analyses and created visualizations using R, Python, and SQL on datasets related to climate change, hydraulic fracturing, drinking water contaminants, greenhouse gas emissions, and home energy use
  • Created a web application for the Army Corps of Engineers to prioritize assets most vulnerable to climate change
  • Developed database applications in Microsoft Access in support of a variety of EPA programs


Neural Network Dog Breed Classifier | fastai, Python, Streamlit
Dec. 2020 – Jan. 2021
  • Created a user-friendly Streamlit application to classify photos of dogs into one of 150 AKC-recognized breeds
  • Scraped approximately 20,000 images of dogs from the internet for training and scoring
  • Used fastai and transfer learning to fine-tune an ImageNet-based convolutional neural network (CNN), achieving a test set accuracy of 53.8%
Python Wrapper for API | Python
Apr. 2021 – Jun. 2021
  • Developed a high-level API to download public comments from
  • Used Python to greatly simplify the download process by handling the complex pagination scheme, API request limits, and layers of requests needed to access comment data


Languages: Python, R, SAS, SQL, PL/SQL (Oracle), JavaScript, HTML, CSS, VBA

Machine Learning: scikit-learn, PyTorch, fastai, H2O, DataRobot

Visualization: D3.js, ggplot2, Matplotlib, seaborn, Tableau

Other: Excel, Access, Git, Linux, Google Cloud Platform (GCP)