I am currently a Masters in Data Science student at the University of British Columbia (UBC) with an anticipated graduation date in June 2024. Prior to pursuing my master’s degree, I worked as a Senior Data Engineering Consultant at Deloitte after graduating from Applied Mathematics and Computer Engineering at Queen’s University.
Although I detail my experiences and skills a bit more formally in my resume, here I’ll share a little summary of the past few years of my life!
Deloitte: Data Engineering Consulting
I graduated from Queen’s University with a BASc. in Computer Engineering & Applied Mathematics in the spring of 2021. Following my graduation, I began working as a Data Engineering consultant with Deloitte in Toronto. Within the Omnia AI team, I specialized in Public Sector technology transformations. My responsibilities varied across projects, encompassing tasks across the data engineering pipeline such as creating data catalogs and data models to guide technology modernization initiatives, writing SQL scripts for data reconciliation, and implementing entity resolution solutions to automate manual processes.
I thoroughly enjoyed leveraging my computer engineering background and problem-solving skills in this role. However, throughout my time as a Data Engineer, I discovered that my greatest interest and passion lay in projects involving data science. With a longstanding affinity for mathematics, I found data science to be the ideal intersection of mathematics and computer engineering, igniting a passion unlike any other I had experienced in my career.
Data Science Masters
In September of 2023, I made the move to Vancouver to start my Masters of Data Science at UBC. After working as a data engineer, I had the foundation in handling large datasets and architecting robust data pipelines. I found the 10-month professional data science master’s program to seamlessly complement my experience in data engineering and background in mathematics. Thus far, I have acquired new proficiency in statistical methods and machine learning algorithms, enabling me to extract patterns and make predictions. I value how the program, given my background, has not only equipped me with numerous technical data science skills but also nurtured my analytical thinking abilities.
Key Courses
- Machine Learning (Supervised & Unsupervised; Classification, Regression, Neural Networks, Language Modelling (NLP), Feature Selection, Time Series & Temporal Models, Deep Learning)
- Statistics (Predictive & Descriptive Statistical Inference, A/B Testing, Hypothesis Testing, Bayesian Statistics, Regression)
- Relational Databases & Database Management (PostgreSQL, NoSQL, MongoDB)
- Data Visualization (Python: Altair & matlplotlib, R: ggplot)
- ML Ops & Software Development (CI/CD, Containerization, Reproducibility, Data Science Workflows, Unit Testing, Automated Workflows)
- Web & Cloud Computing (AWS, Spark)
- Data Structures & Algorithms
- Data Privacy & Ethics
