Data Science Intern
My intern project was to tune the hyperparameters of a probabilistic data structure, the Vector of Counts, that the team proposed to use for forecasting. When The Trade Desk does forecasting, there is a policy that only up to 90 days of historical user data can be stored. This makes long-term forecasting difficult. The Vector of Counts aggregates the data so that more than 90 days of data can be stored while still protecting user privacy. My project helped enable long-term forecasting to understand seasonality and long-term trends.I used Databricks to write code for hyperparameter tuning using Spark Scala, and it is in a GitLab repository for future use. By analyzing the data that was generated when I ran the code to tune the hyperparameters for key Vector of Counts operations, I determined the best hyperparameter values. I wrote several Confluence pages (webpages used by The Trade Desk) documenting the results. The tech lead on my project will continue to work on the project.