Data engineer with bachelors in physics and comprehensive research experience. Interested in building robust data pipelines, working with complex data schemas and working directly with users to perfect systems.
REsurety is the leading analytics company empowering the clean energy economy. Operating at the intersection of weather, power markets, and financial modeling, we enable the industry’s decision makers to thrive through best-in-class value and risk intelligence, and the tools to act on it.
With the world’s leading clean energy investors, advisors, buyers, and developers as clients and 7,000 MW of transactions closed, REsurety empowers clients to thrive in the dynamic, complex, clean energy-fueled future.
Fellowship program to learn the fundamentals of data engineering through a self-designed project using AWS architecture
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Built MigrationPlus, a distributed pipeline to join location/timestamp sensor data from animal migration studies with current weather conditions, allowing researchers to enrich their data collection
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Accessed data files in S3, processed 40GB of historical weather data with Spark and stored in PostgreSQL with PostGIS indexing to join the datasets
Improved functionality on a healthcare fraud detection solution with realtime and post-pay detections and analytics
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Programmed ETL from XML and flat data files, queried data, generated reports using SAS and SQL
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Added automated processing and audit logging for fraud investigation cases from 3 organizations to an application to match existing front-end processes resulting in a comprehensive case tracking system
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Saved $1 million per month in denied prepay claims by implementing a detection determining an overlap in coverage
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Communicated directly with the client to determine focus areas and deliver a solution that meets their needs
