I am currently the head of Automatic Voter Registration and Fundraising at Data for Progress. Previously, I was the Development Manager for New Era Colorado, the state's largest young voter mobilization organization. In addition to my responsibilities as a fundraiser, I was the the resident data nerd at New Era, assisting with everything from writing scripts to clean messy CSVs to analyzing the success of our fundraising programs. Leveraging the insights from a statistical analysis of New Era's monthly member program, I developed a re-imagining of the program to double the revenue within a year.
In 2018 I was accepted as a Data Science Fellow with Springboard, an intensive 600-hour, 6-month bootcamp to kick start my career in progressive analytics. Inspired by my time living in Denver's historic black neighborhood, my first capstone project predicted gentrification in Denver, Colorado. I then chose to specialize in Deep Learning and developed a neural network to classify rooftop area from satellite imagery to promote rooftop solar.
Prior to my work at New Era I was the Executive Director of Engineers for a Sustainable World where I led an international organization, tackled messy sustainability challenges, and used data science as a tool to drive social change. As a firm believer that people can engineer change, I used my data analytical know-how to uncover valuable insights behind the need and impact sustainable projects have in communities worldwide. I also developed and launched Build Day—a flagship national program that brought together more than 500 community members and 100 volunteers to design and build sustainable projects in disadvantaged communities across North America.
Data analytics Visualization Machine Learning CRMs
Grant writing Fundraising strategy & planning Digital fundraising
Director of Automatic Voter Registration & Fundraising
Data for Progress
I currently work at Data for Progress leading their research on automatic voter registration and leading their fundraising operations.
Board Member & Project Manager
I co-lead MiDataLabs, a for-profit company that provides data and programming expertise to non profits. I am responsible for project managing the team and leading our sales operations.
New Era Colorado
Lead fundraiser for a $2 million organization that engages young people in democracy to build a better Colorado.
Engineers for a Sustainable World
Executive Director of an international sustainability nonprofit with over 50 chapters at universities.
Diversity of jobs created by the Green New Deal
Won a grant from Data for Progress to research the diversity of jobs created by the Green New Deal: who gets these jobs, what do they look like, and where do they live?
Neural Net to Identify Rooftop Area for Solar Policy
Independent final capstone of a convolutional neural net to classify rooftop area in Denver.
Built a data generator to apply random cropping and rotations to 100+ hand labeled data.
Constructed and trained a convolutional neural net architecture based off the U-NET architecture.
Ran the trained model on all 1,800+ satellite images for Denver, CO to determine the total estimated rooftop area in the city, then determined that full solar coverage of all rooftops in Denver could not meet Denver’s residential electricity needs.
Springboard Data Science Fellowship
Completed curriculum including Python for Data Science, Data Wrangling, Data Storytelling, Inferential Statistics, and Machine Learning.
Used linear regression with sklearn to determine features that best predict Boston housing prices.
Performed three exploratory data analyses using Python that included techniques such as hypothesis testing, one-sided t and z tests, and bootstrapping.
Investigated a drop in Yammer user engagement data using SQL and concluded that a broken link in an email was the culprit to the dip.
Predicting Gentrification in Denver, CO
Independent capstone for Springboard that included data wrangling, statistical analysis, and machine learning.
Downloaded and cleaned data from both the U.S. Census and data queried from Yelp’s API.
Visualized the relationship between point data of new restaurants and cafes and spatial data of gentrified census tracts in ArcGIS.
Applied inferential statistics to determine if there was a significance between the number of new cafes and restaurants in a census tract and whether that tract had gentrified.