James Knopp

Navigated expansive Teradata and Google Cloud databases by writing complex SQL queries to efficiently extract data and update tables

• Created convolutional neural networks in Python to accurately predict customer ordering thresholds based on features such as average monthly purchases, region, product, and yearly script count
• Developed interactive Tableau dashboards providing insights that allowed management to focus on which products could benefit from threshold updates, which helped increase customer retention by 12%
• Developed and maintained automated SAS processes that provided helpful data to various teams on a scheduled basis (weekly cut order reports, monthly ordering percentiles, etc.)
• Identified errors in existing data pipelines that would upload duplicate records into the company database
• Successfully troubleshooted and rebuilt the data pipeline to upload only distinct records to the database.

• Worked on various AML projects such as credit card fraud, transaction monitoring, and money laundering
• Reviewed large sheets of data in Excel and utilized analytical skills to determine transactions that were fraudulent or inconsistent with the customers normal spending habits
• Appropriately drafted SARs for accounts being used for unlicensed MSB activity, money laundering, and credit card fraud
• Kept all customer bank account information confidential by following strict security protocols.