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In my current role I help and lead data analyses of internal audit intiatives within the Ontario Public Service (OPS). My duties include designing and creating engaging and interactive dashboards to be used by auditors and audit clients in PowerBI, cleaning and modelling the data using PowerQuery and DAX. I regularly use a variety of data connection methods, having grown familiar with SQL and OData queries, and RESTful and SOAP APIs. Additionally, I have led initiatives to explore the use of predictive analytics in audit, in training and deploying natural language processing (NLP) text analytics models to label audit data.
I assisted the creation and development of data pipelines to ingest water content data from an inhouse Java web application using SQL and Informatica, greatly improving data collection and processing over legacy systems. Led rounds of data validation and performed analyses to ensure proper data integration. Designed and performed multiple rounds of QAT and UAT on web app to ensure data security and governance standards were met.
I led multiple rounds of data cleaning and validation on public clinical research data using pandas and NumPy in Python. Provided comprehensive data analysis using R. Presented summary visuals using matplotlib.
This dashboard served to present national census data across Ontario in order to give demographic context on Ontario’s regions to drive audit projects. The data is sourced from the 2021 national census and connected to PowerBI via OData Query.
Public [Provincial Court data] (https://www.ontariocourts.ca/ocj/statistics/) was summarized and analyzed to highlight potential issues within the Ontario Courts system. Analysis included measure of court case backlog month over month and highlighting outliers in average days to case disposition statistics.