Faria is a Master of Information Candidate at the University of Toronto’s Faculty of Information.
Her research interests lie in the application of Process Mining technologies on email-driven business processes.
Hello! Welcome to my website! You can find out more about me through my social media links or by just scrolling down!
Click on “Projects” to see my work and scroll down to the “Blog” menu to read my thoughts and experiences on personal milestones and data science related topics. Feel free to get in touch with me using the “Contact” page
I graduated with an Honour’s Bachelor of Science degree from the University of Toronto, double majoring in Anthropology and Human Biology. My interest for all things Data Science started after my undergrad and I have many amazing people to thank for helping me discover this passion and make this career transition. As a generalist, my skill-set borrows from a wide range of fields: from Business Process Modelling, to Data Analytics and Machine Learning to managing customer and stakeholder relations. It has been a very challenging, yet extremely thrilling journey!
View my most up-to-date resume here
What does it mean to be a ‘Data Archaeologist’?
I first came across the term “Data Archaeologist” during a session of the Toronto Data Workshop (which I previously co-hosted with Professors Kelly Lyons and Rohan Alexander). To me, it just seemed like the perfect way to describe how I see my role in the field of Data Science.
An archaeologist uses tools and knowledge of the past to discover the story behind historical artifacts and sometimes, those historical artifacts helps to expand the historical knowledge.
In a similar manner, data scientists also work with tools to derive insights from historical data and those insights oftentimes expand the domain knowledge.
The data science spectrum is broad and I have not yet been able to narrow down my interests with regards to specific roles. Which is why Data Archaeologist and all the connotations it carries, is the only way I prefer to describe myself.
When I’m not up to my neck in my course readings or StackOverFlow posts, attempting to debug my code, I enjoy reading and retweeting Data Science related blog posts, sharing memes, going to the gym, travelling with my family and friends (well, because of the pandemic, I’m just adding things to my bucket-list now), watching documentaries, movies and comedy specials and sleeping. I am most active on Twitter and Instagram where I post about my day to day happenings as a grad student!