Stamford, Connecticut, United States
Jane graduated from New York University in 2020, with a master's degree in data science. She is a Data Scientist at GeneDx, specializing in deep learning and machine learning.
● Multi-objects Recognition Model: Performed data augmentation on limited availability amount of data in Python and improved the object recognition model accuracy to 94.2% ● Object Annotation Model: Assisted in the implementation of new neural network algorithm Polygon-RNN that predicts object contours to automate annotation process ● Optimization: Optimized and documented Python scripts that enabled large data processing
● Organized and summarized claim data for over 20 types of vehicles to develop research objective regarding claim rates in the Chinese market ● Tested the completeness of data sets using R to validated census data
● Developed visual analysis dashboards in Tableau and Excel for client executives to examine physician expenditure data ● Assessed and evaluated census data from 20 clinics to calculate premium factors for pricing health plans ● Redesigned data retrieval tool and implemented new graphical analysis function, increasing efficiency by 30% ● Programed data extraction codes in Excel to generate reports automatically from two datasets ● Reconciled and summarized claim data over the past ten years for 1,000 policies to generate loss reports for three clinics