cv
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Basics
| Name | Daniel Gause |
| Label | Data Scientist and Astronomer |
| danpgause@gmail.com | |
| Phone | (207) 249-0392 |
| Url | https://dangause.github.io/ |
| Summary | A data scientist and aspiring astronomer with extensive experience in machine learning, data engineering, and data visualization. Tangential research in botany and remote sensing. |
Work
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2021.05 - Present Data Scientist
Accenture Federal Services
Data scientist at the consultant level at Accenture Federal Services. Built and maintained dozens of full-stack ML/AI packages. Led small teams on research-driven projects.
- Maritime Vessel Pattern-of-Life Classifier: Developed an ML pipeline trained on historical NASA satellite imagery data to predict wildfire, flood, and landslide risks, enabling ESG monitoring and impact management of climate change effects on natural resources for IDB Invest in Latin America.
- Synthetic Data Generator: Lead developer of microservice Python package that automatically generated a synthetic datas- cape based on PII data, utilizing NLP, LLMs, and retrieval-augmented generation
- United Network for Organ Sharing Predictive Analytics: Built, tested, and deployed a CI/CD ML pipeline using survival analysis machine learning predictive models trained on >10M rows using Apache Spark to predict kidney transplant waitlist survival time.
- E. Coli Outbreak Predictor: Developed a pipeline using DBSCAN to spatiotemporally cluster CDC and NOAA weather data and trained a Random Forest to predict localized E. coli outbreaks from tropical storms
Volunteer
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2024.12 - Present Santa Cruz, CA
Image Reduction Pipeline Development Volunteer
University of California Observatories
Volunteer developer for the Nickel Telescope.
- Assisted in the development of an automated astronomical data processing pipeline for Lick Observatory's Nickel Telescope
- Built astronomical image reduction tutorials in python for observatory outreach
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2024.05 - Present San Francisco, CA
Scientific Computing Department Volunteer
California Academy of Sciences
Volunteer at the Scientific Computing Department at the California Academy of Sciences.
- Assisted in the development of parallel processing for a citation finder application
- Utilized NLP and spatiotemporal clustering techniques to analyze historical specimen data
Education
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2016.09 - 2020.05 Middlebury, VT