Andrew Faris Email and Phone Number

Used Python to automate generation of the weekly Conventional Mortgage Market Indicators report which is circulated to the over 50 people within the departmentInformed the department’s decision making in renewal of a $100,000 yearly subscription to a mortgage securitization database.Used the Dask library in Python to convert large (>10 GB) SAS data files into Dask dataframes for processing in pythonCreated data visualizations on subsets of the both internal and external datasets to better understand their respective market coveragesPerformed data-deduplication after combining internal and external datasets

Worked in the Department of Enterprise Regulation in the Office of Models and Methods (Models Branch). Responsibilities included developing data visualizations to better track and assess the risk levels of both Fannie Mae and Freddie Mac's financial models