Hawkfish Tech: Our 2020 Election Cycle Efforts

Photo by David Clode on Unsplash
  • Accurate election forecasting with massively parallelized and novel machine learning
  • Cost-efficient GOTV campaigns via our support and turnout models and early vote data
  • Highly optimized persuasion campaigns through our Looking Glass tool
  • All of the above enabled by high-quality voter data and infrastructure
  • Identification of 7 million previously untracked unregistered voters
  • An increase of 10 million phone numbers and 40 million email addresses to improve voter contactability and platform match rates
  • A 10% increase in demographics accuracy for race and education and a 25% increase in sub-ethnicity classification accuracy
  • Identification of 31 million Democratic donors and 69 million progressive issues donors, each representing vast increases over individual input data sources.
  • We balanced flexibility with an opinionated framework. By using Docker and Kubeflow Pipelines (KFP), data scientists had the ability to both choose their stack or use a default suite of reusable KFP components (via Sci-kit Learn Estimator API).
  • We developed a Model Quality Control Dashboard in Plotly to provide a suite of diagnostics including: User-defined evaluation metrics, HiPlot parallel plots, Partial Dependence Plots, SHAP Plots, and Conditional Score Distributions.

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Hawkfish

Hawkfish

A powerhouse of technology, data science, and creative innovation in support of progressive causes.

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