From Electrical Engineering to a Fintech Unicorn | Outliers
Welcome to Outliers, where we celebrate the rebels that are shaping emerging tech. We ask developers and engineers how they came into the tech space, what gets them excited, and what cool shit they’re building.
Meet Varun Hasteer, a Senior Data Developer at Neo Financial, Canada’s newly minted unicorn company. Like many developers, Varun didn’t start his career as a developer. Varun studied electrical engineering and worked in software development support for 8 years before finding his calling as a data developer. Today, Varun is a true outlier in Canada’s fintech space, using his machine learning and predictive modeling solutions, Varun helps Neo Financial break into new spaces and make banking more enjoyable for Canadians.
What do you do?
I’m a senior data developer on Neo Financial’s advanced analytics team. When I originally joined 7 months ago, I worked on the data engineering team, where I built data pipelines to improve our understanding of our customers. Now, I’m more involved in machine learning and building predictive models.
Why work as a data developer?
I studied electrical engineering and wanted to work in tech, particularly in software development. I had always taken computer science electives in university, so I knew how to code. When I started my career, I worked in support roles related to software development, but I wanted to build something myself, so I studied a lot on my own and completed additional programming courses.
What made you want to work with Neo?
I like having an impact on people’s everyday lives, and it’s a good challenge for my tech skills to solve problems at a rapid pace. There’s a sense of importance and immediacy that comes from working with people’s hard-earned money. The pace of Neo’s growth was really impressive to me — after I first heard about the company, I kept up to date with their press releases and what they were building, and wanted to be part of that hypergrowth by building fast. And now we’re a unicorn company after just three years!
What are you building at Neo?
Right now I am building a model for the customer onboarding team, which is a machine learning model that will help us make predictions about customers. Machine learning helps verify customer details, and automation saves a lot of time for our team so they can concentrate on delivering the best possible experience for our customers.
What’s the most exciting part about what you do?
Building new products is the most inspiring thing, and it’s amazing to see what other teams around me are working on. In my own work, I haven’t built anything like this new model before, so it’s really cool to build from the ground up and see what the tech is capable of.
What sets your work apart from similar roles at a non-startup?
The pace is the biggest difference, and that comes into play when we’re talking about the technology used. Established companies built their infrastructure years back with technology that is now old, so it’s a huge pivot for them if they want to move to cloud and use the latest tools and technologies. Startups like Neo don’t have that problem. It’s exciting, knowing you are using the latest tools in the market, and that the technologies are in high demand.
Another thing about the tools that non-startup companies are using is that they require a lot of coding, with a team that builds the infrastructure but doesn’t actually deploy it. At Neo, if there is a model that a data scientist like me has built, anyone can deploy the model. Our tech stack is very user-friendly, so it’s easy for new people to join our team and start building.
How do you stay up to date with the latest technologies?
Technology evolves quickly. One example is Hadoop, which is an open-source framework that was previously very popular, but it was soon replaced by Apache Spark. Hadoop needed one hundred lines of code just to process one or two megabytes of data, but with Spark, you can do the same thing with just two or three lines, which moves projects along faster. One of my favourite things about Neo is that we use the latest technologies as much as possible.
To keep up to date, there’s some things that you need to learn on your own, but there are so many great post-graduate programs or certificate programs out there. The documentation on the websites of new tools is super helpful. One of the best resources is Kaggle, which offers datasets that you can learn from. Those are really fun, because sometimes they have competitions, where you use a dataset to build a model and win cash prizes!
How has working at a tech startup helped you grow as a developer ?
When you’re building something new for a startup, part of that process is failing fast. When you fail fast, you learn fast, and it helps you grow and build your company. Failing doesn’t sound good, but it’s an essential part of the learning process, and treating issues as an opportunity to fix things really helps me get in the right mindset to grow my skills and master new technologies.
What has helped you grow as a leader in emerging tech?
One thing that’s helped me a lot as both a developer and a leader is taking a fail fast approach and putting together demos to ensure our team is constantly learning and growing as we build. Whenever I build, I put together a presentation that outlines what the application will do, how it will work, and how it will be more effective than whatever we are using now. When you’re sharing knowledge in this way, it helps ensure that you’re building together. which is essential for a fast growing startup like Neo Financial to be able to break into new spaces and build something that pushes the envelope.
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