May 2022 - Present

Data Analyst @ EverCommerce

• Leading the creation of a self-service AWS QuickSight module for managers across 300 mental health agencies using ETL methods to transform large mySQL databases to PostgresSQL data warehouses for on-demand analytics. • Developing regression-based machine learning models using XGBoost libraries to predict workflows, and service statuses on 75 calculated measures needed for regulatory reporting to Ministries and accreditation boards. • Conducting large-scale data migrations from legacy systems into company software using SQL Server to consolidate and prepare data for loading and leveraging relational database design systems to accurately ingest data for 7 large clients with millions of rows of protected health information (PHI).

May 2023 - Feb 2024

Data Engineer @ QuantaEstate.AI

• Cultivating data pipelines directed to S3 data lakes by building out key components in AWS Glue to deliver daily data of 700,000 real estate properties across the United States using APIs from multiple relational databases. • Processing data using big data tools such as Hadoop and Spark for machine learning algorithms from unstructured datasets, reducing the data modelling time investment by 37%. • Improving the accuracy of the model in predicting real estate prices by tuning hyperparameters with scikit-learn (for smaller models) and Apache Spark MLlib (for bigger datasets) by 12%.

Oct 2019 - May 2022

Data & Research Specialist Intern @ Medical Makers

• Performed data cleaning, data-analysis and data visualization tasks on echo cardiogram, respiratory, and nutrient data as part of the Canadian Space Agency’s Deep Healthcare Challenge to prime 8 datasets for modelling. • Cultivated directives to build a computer vision analysis strategy to improve a disease detection algorithm accuracy from laboratory images by 19%. • Visualized data through Seaborn and Tableau, disseminating information to a team of over 15 experts of various backgrounds on the findings of the data analysis.