100% student-run organization which manages a $2 million endowment fund

- Developing data pipeline to automate daily transaction reporting to state DMV's- Handling over 100,000 daily transactions- Utilizing Apache Spark, Scala, and AWS Glue to filter, join, and process distributed dataset

-Extracted radial velocities from frequency data collected by IRAM 30m telescope for two dozen molecular clouds as part of LEGO molecular cloud survey-Devised & documented more efficient method for computing kinematic distances; calculated distances to compare luminosity estimates-Presented documentation at Northeast Star & Planet Formation Conference

Under the direction of Dr. Jens Kauffmann, analyzed data from the LEGO molecular cloud survey to gain a greater understanding of the properties of molecular clouds in the interstellar medium and star formation rates within those clouds. More specifically, utilized astropy and other python libraries to produce figures on integrated intensity, velocity dispersion, line ratio, and several other critical metrics across a range of molecular transitions.