Quantitative Developer Intern
May 2021 - August 2021
internship
Developed a Gradient Boosting Machine model to bypass the time-consuming CTE calculation of the liability simulation model used by the Variable Annuity Hedging team. This improved the team's efficiency and ability to more quickly inform the company's investment decisions.
An app to help patients find clinical trails
Hack The North January 2021
hackathon
Clinic Connect is a patient-facing clinical trial platform that allows for patients to search for nearby trials based on a variety of parameters. The purpose of the app is to help clinical studies overcome the major problem of lack of willing participants. Won the Finalist Award !
An insurance gamefication client
PennApps September 2020
hackathon
Developed Insura, an IOS app that acts as a platform to interface between insurance providers and homeowners in order to incentivize the adoption of safe housing practices using gamification. Won 1st Place Insurtech by UPenn Wharton Risk Award !
UI/UX Designer
August 2020 - December 2020
club
In Design Innovation, I collaborated with team members to assess our client's needs and to conduct research on their target market to develop the user interface for their Multual Aid mobile app that will provide an enhanced user experience.
Quantitative Developer Intern
June 2020 - August 2020
internship
Worked in the Variable Annuity Hedging Team to develop and optimize a real world Economic Scenario Generator. Additionally designed and implemented a visualization tool to study the economic paths underpinning the CTE of the VA liability surplus projection.
A tool to inform flu vaccine production
HackPrinceton November 2019
hackathon
Flulytics is an application that aids flu vaccine production by using predictive analysis to identify likely sites of mutation in the influenza strain from year to year. Won 2nd Place Overall and 1st Place Facebook Award !
Data analyst intern
July 2018 - August 2018
internship
At the Columbia University Medical Center, I worked in the Xu Lab to develop a pipeline consisting of R scripts to analyze SC-RNA data collected from stem cells in the lab for neurosychiatric disorder research. To achieve this, I utilized t-SNE dimentionality reduction and clustering methods.
