• Backend Engineer in Gemini's Retail/Growth/Onboarding space

• Led the backend development to improve Gemini's UK onboarding flow for users and auto approval process, which increased our UK conversion from 17% to 35% and auto-approval rate from 49% to 86%

• Localization work to increase access to Gemini to over 10 new jurisdictions, and also further improving existing jurisdictions onboarding process

• Adding self-service solutions for users to improve user experience and drive down CS tickets

• Stepping in as interim lead developer for redesign and overhaul of Portfolio Metrics feature which included:

• Redesigning and restructuring the planned to follow better coding practice

• Data engineering and mining for large gaps in data, adding caching, and working with all

stakeholders to figure out how to deliver this product despite many delays

• JPMorgan's Software Engineering Program Class of 2018

• Spearheading and leading a data mining initiative focused on extracting patterns and customer segmentation

• Created a dashboard for trend analysis and time series forecasting to understand the impact of COVID-19

• Performing unsupervised learning across time series and cross sectional data consisting of millions of data instances; automating the extracting, transforming and learning pipeline

• Developed a Kafka engine from start to production on a fully Agile team

• Collaborated with architecture, infrastructure, developers, and management to design and implement a data streaming engine and a analytics engine

• Created proof of concepts for new technologies and presented their value to technical and business audiences

• Technology stack: Kafka, Scikit-learn, Pandas, Dask, GraphQL, Tensorflow, Flink, Dash

• Languages: Python, Java, R, Node.js

• ETL Pipeline - parsed data from online resources, cleaning/normalizing data, and using geographical/census data to proxy for missing variables

• Analyzed the data by visualizing trends across the university

• Conducted a comprehensive statistical analysis using R on panel and time series data, using paired t test and multinomial logistic regression to measure.

Under Professor Bill Harbaugh and the University of Oregon's Senate Course Evaluation Task Force. My research focuses on calculating the determinants of Standard Evaluations of Teaching at the University of Oregon, particularly focusing on gender and country of undergraduate study. This project is an extension of my thesis research.