The Final 6 | ENJINE’s Jin Choi

Blog March 3, 2021

Posted by Harrison Crerar

The Final 6 | ENJINE’s Jin Choi Featured Image

The battle is on. Things are heating up. And our top 6 have been chosen.

We met one-on-one with the 2021 OKGN Angel Summit’s top 6 to hear their insights into the Summit and their final pitch for the top spot.

Meet Jin Won Choi, founder of ENJINE in Kelowna. Jin has created a machine learning algorithm that maximizes investment strategies. We recently caught up with Jin to learn more about his inspiration behind the idea, his experience as an entrepreneur and his plans to go the distance in the Summit.

What inspired you to start ENJINE?

It started half as an intellectual challenge and half as a way of making money. The intellectual challenge was that there is a lot of skepticism in the industry about whether machine learning can be used successfully to create investment strategies. A lot of people have tried and failed. For me, this was very puzzling because it should work. I had the opportunity to try solving this challenge through a consulting project and, in that client’s case, I succeeded. In order to make it work, you need a deep understanding of machine learning. You need to build the models from the ground up—which is an extremely rare skill. That’s what sets ENJINE apart.

Why should your clients be excited about your machine learning investment strategies?

What we’re doing is very interesting because it harnesses the power of compound growth. Something that grows exponentially can become something quite big. In terms of wealth creation, compound growth is extremely valuable. What we’re trying to do is increase that compound rate of growth significantly over traditional means of investing.

Can you tell us about the success you’ve found?

We are working on an algorithm with an asset manager in the states—someone who creates financial products, packages them up and makes them available for sale. Our backtest of that fund, which is a simulation of how the algorithm performs, is looking really promising. The latest one indicates that it would have created a 20% per-year compounded rate of growth with only a medium level of risk.

What kind of expertise is your team bringing to ENJINE?

I have a PhD in financial mathematics and industry experience working on hedge funds, creating financial and machine learning models in different contexts. I’m an expert in the field and have a patent in the field of machine learning. Our co-founder has a similar background, and we have another team member who is highly mathematical and experienced in the financial field. We have our fair share of financial geek cred.

How do you see your company growing?

Our plan is to find partners to launch funds with, backed by different machine learning investment strategies. We see ourselves launching only a few funds per year. I don’t think we have the capacity to launch any more than that, nor do we really want to—considering each of these financial strategies will take a lot of our brainpower.

If you were to win, what would you do with the investment?

That investment will go towards hiring someone new. We have a lot of plans to enhance our strategies and create new ones. To do that, we need new people to join our team.  We want to grow carefully, not quickly. Talent in this space is very scarce and we only want to onboard the best people to our company.

What has this experience taught you about the entrepreneurial journey?

This experience has been fantastic for me. I feel like I know how to communicate my message better to potential investors now. I’ve relearned how to connect with investors and learned what they don’t know, what they do know, and what they care about.

What surprised you most about participating in the OKGN Angel Summit?

I was surprised by the number of people who are trying to incorporate machine learning into their business models, and I think that’s great. One thing that I learned that we need to be careful about is how to differentiate our machine learning from other types of companies who are using machine learning. We go much more into the mathematical weeds. Other applications don’t necessarily need to, which is completely fine. You don’t always need to invest in your own model if some off-the-shelf solution does the job.

What advice would you give to the participants of next year’s summit?

Tell a story. There’s a template of all the slides that you need to put in for a pitch. In general, I think that format works because it covers all the bases. But, when you talk about the contents of those slides, try to weave all the points into a story so that it’s more accessible to the investors instead of treating them like bullet points.

For tickets, more information, and a complete list of the participating companies, please visit

Connect with Jin. Learn more about ENJINE.

Meet the other finalists:

The Final 6 | TechBrew Robotics’ Mike Boudreau >>

The Final 6 | Streamline Athletes’ Brett Montrose >>

The Final 6 | Live It’s Melissa Welsh and Mike Irvine >>

The Final 6 | Beyond Aerospace’s Mike Ball >>

The Final 6 | RocketPlan’s Joe Tolzmann >>

Related Reading