Text Analysis of Securities and Exchange Commission Comments and Rules

We have a database of several thousand comment letters and rulemakings of the Securities and Exchange Commission during recent decades on a range of securities regulation issues and would like to use machine learning and NLP methods to analyze the relationships among various comments and the language in those comments with both proposed and final rules over time. The database is more than a gigabyte so we need someone who has the ability to help manage a database of this size. These topics are of significant research interest and include a wide range of financial market research questions, including questions relate to climate disclosures, short selling, securities trading, and other regulatory issues.