Leveraged data from multiple sources (Domo, Google Analytics, Google Ads, Adobe Analytics, Adobe Target) to provide valuable insights for our marketing and executive teams. Major projects included a national overhaul of the customer membership program, where historical data was used to identify the characteristics of top performing plans and preparation of suggestions for optimization.Facilitated on-boarding of dozens of domains to Adobe Analytics, developing reports and training end users on the tool. Developed MCC reporting format for use in enterprise-level reporting.Made contributions to analytics strategy at the organization, emphasizing the use of scalable analytics (notably MS Azure, PowerBI, and Adobe Analytics) a commitment to narrative-based analytical insights, and implementation of a sprint cycle for analytics work.

As a data science consultant, I performed analysis of HR data to ensure data integrity through migration to Workday HCM. Gathered data requirements and contributed documentation to establish proper data structure for later analysis.

I delivered business insights to Sales and Finance departments, employing a mix of machine learning, data visualization, and presentation skills. Projects of note include a multivariate volume forecasting model to improve order forecasting and a large scale automated web scrape of competitors websites using Selenium. The resulting competitor density data was used to inform sales staffing decisions, significantly contributing to future revenue.

I was tasked with generating insights from large datasets for our clients, which included leading real estate, finance, and government organizations. Analysis was performed in Python, SQL, R, Power BI, and Excel. During this time, I wrote hundreds of analytical reports, gave hundreds of presentations to clients, and conducted high quality ad hoc analysis for clients. Wrote machine learning programs to forecast and analyze data at scale.

Established and led Canadian Multifamily Research group as our organization expanded research and marketing efforts into Canada. I led a team of 3 researchers, and was responsible for the allocation of available resources to meet expansion deadlines. Used SQL and Power BI to build a reporting suite to manage our research efforts. Our work resulted in thousands of new added properties and contributed to the successful launch of Apartments.com in Canada.

Developed a Python-based movie recommendation model under the mentorship of a local senior data scientist. Applied content-based and collaborative models to the MovieLens dataset. Upon completion of the project, our team presented our results to an audience of peers and industry professionals and was awarded the honor of Top Presentation for our efforts.

Internship with CBRE's analytics group where I contributed to quarterly commercial real estate market research. In this role, I developed professional writing and analytical skills.

Worked in a number of roles involving computer and mobile phone sales. Developed retail sales and client relationship skills.