My first virtual co-op with SharpestMinds!

I’ve just finished a virtual co-op with SharpestMinds. It was a completely new kind of experience for me, and I thought it would be worth sharing.

First off, a bit of background. I’m completing a Electrical and Computer Engineering Master’s degree (with a focus on machine learning) at Carleton University in Ottawa, Canada. I first heard of SharpestMinds through a physicist friend of mine, and joined the platform a few months ago.

A few weeks later, I applied for a virtual co-op posting with BigTerminal, a Toronto-based fintech startup that wanted to start using their massive inventory of data to predict changes in interest rates set by the U.S. Federal Reserve. For this project, I was paired with Tony Lin, a Ph.D. student in Physics at McGill University in Montreal. Tony and I both had a fair bit of prior experience working with various machine learning frameworks, and wanted to apply what we knew to some real industry data.

It was Tony’s and my first time working on a project with SharpestMinds, and we were new to the dynamics of working as contractors, and the virtual co-op concept. However, our SharpestMinds mentors were very helpful in answering any questions in the set-up phase of the project and we got comfortable with the workflow very quickly.

The process started with an introduction call to connect with BigTerminal, after which we were provided with the authorization credentials and data we needed. Weekly check-ins allowed us to report how we were progressing on each week’s deliverable. The milestones and deliverables are clearly set at the start of the project and agreed upon by both sides, which helped us to quickly gauge the amount of effort needed to complete the project, and to tell whether we’d be able to take it on.

Just as with any research project, challenges arose that we needed help or support to address; the SharpestMinds team were always available to discuss, and suggested fixes that would help us move past the problem. They were also available to liaise with the customer when there were clarifications to be made on the deliverables or the timeline.

Working with SharpestMinds was a really great learning experience; we were able to apply our skill set in machine learning and critical thinking, as well as learn concepts that underly time series data. The learning toolbox that they provide is also a great resource for beginners and intermediate practitioners and it provided a great foundation to start off the project.

Although we’d both had plenty of experience with machine learning tools prior to the project, we’d never worked on an industry problem before, or had the chance to work with time series data. We covered a lot of ground through the project, and we learned and applied tons of tricks that were specific to time-series data, like de-trending and compensation for seasonality and other effects. Because the project started with a literature review phase, we were also able to pick out cutting-edge strategies that had worked for similar problems before, and test them out on the BigTerminal data. By the end of the project, we’d thoroughly explored the problem space, and produced a solution which was, as far as we’ve been able to tell, novel and state-of-the-art.

I had a great time with my first SharpestMinds virtual co-op, and the real-world experience it provided us has definitely put us in a great position for the post-graduate job hunt. I can’t think of a better way to make the academe-to-industry transition.

Editor’s note: if you’re interested, you can apply to SharpestMinds here.