Self-starter individual able to apply data analytics and machine learning in finance and accounting processes to innovate where possible
Full-time parent of my siberian husky
Bachelor's of Honors Specialization in Accounting (Western University)
Data analytics and machine learning post-graduate certificate (Mohawk College)
Currently learning : neural networks conceptually and applying it on toy datasets using Keras (CNNs, RNNs)
Podcasts : Pivot, CBC Frontburner, The Strategists
Video games : Battlefield 4, Warzone, No Man's Sky, Humankind
Excellent listening and note taking ability
Desire and willingness to learn
Analytical decision making skills
Working with energy and empathy
Business storytelling skills
Good awareness of ethical concerns and stakeholder management skills
Working within tight schedules and delivering high quality results at the same time
MS Excel: SUMIF, COUNTIF, VLookup, PivotTables and Charts
MS Word, PowerPoint presentations, Git, Google Suite
Working knowledge of PowerBI and Tableau
Data analysis and cleaning in Python and R: Intermediate
Machine Learning in Python and R: Beginner (Linear Regression, Random Forests, KNearest Neighbors)
Applied ability to innovate traditional processes through digital automation and find patterns in data using machine learning
Certified Predictive Analytics Modeler : Creating Predictive Analytics Models using SPSS
Certified Business Intelligence Analyst : Building reports and dashboards using Cognos Analytics 11.0
Investment Funds in Canada from Canadian Securities Institute : In-depth understanding of the mutual funds market. Able to analyze the risk-return relationship of the investment and effectively manage client portfolios.
The MNIST Handwritten Digits Recognition Database is a collection of handwritten digits images. The report I have created is uploaded in PDF format and describes the dataset and the process that was used achieve the modelling results in the end. This is a fun dataset to play with and get started with computer vision Machine Learning problems. This project was completed in Python.
Conducted exploratory descriptive analysis on the Netflix Movies and TV Shows database available on Kaggle.com. Used R programming language and multiple packages to create visualizations and gather insights about the data.
Analyzed data sets created from open sourced data found online on the Canadian real estate market and housing affordability. The resulting poster provides recommendations on investing in the housing market and how affordability has changed due to the pandemic.
PwC Canada
Assurance Specialist
H&R Block
Tax Professional
Mohawk College
Analytics for Business Decision Making (Post Grad)
Western University
BMOS Honors Specialization in Accounting