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  • Writer's pictureSheldon Lewis

My Time at Interac - Software Developer Internship, Winter 2023

Updated: May 10, 2023

I’m sad to announce that my time at Interac Corp. as a Software Developer Intern has come to an end, but I'm here with you today to document my term! This being my first post, I'm excited to finally get started writing down my memories, learnings, and experiences, for the world to see and for myself. This style of writing and sharing my experiences is a skill I want to build, and soon I'll be getting into showcasing exciting innovation and development, and sharing my thoughts and opinions on what's going on around us and in my world. This means tech, finance, AI, volunteerism, environmental/social issues, mental health, whatever I experience and want to share. And we're starting off with my first internship!


The term was better than I could have hoped, starting with being lucky enough to get an opportunity to work a software role at one of the most innovative fintech companies in the world that's constantly producing new and exciting technology, dominating the payment services landscape for several reasons that make it such a great place to learn from, especially given my quantitative and finance-centric interests when it comes to development. I have a lot of people to thank for my 4 months that were unforgettable, because of both that perfect learning experience and my incredibly supportive community. Your mentorship has given me my ideal launch into the tech and finance sectors, the software industry, and my professional life. Anyways, let's get into the technical:



I spent the term programming with the Real-Time Decisioning (RTD) Team, working with our advanced system that uses machine learning to instantaneously determine the probability of fraud for each and every one of the millions of debit and e-transfer transactions, based on hundreds of minute details per payment. The system then determines the appropriate course of action using that probability. A special shoutout to the incredible RTD squad, and a huge thank you to Jason, Sarita, Kavya, Jalaj, Satrajit, and Lili for each taking the time to take me under your wing and mentor me, I hope you can see how much you've helped me grow.


Going back, I was pleasantly surprised to be assigned an ML-focused modernization proof-of-concept as my main project for the term. I wrote code to determine the feasibility of enhancing the fraud detection and scoring system, replacing older infrastructure with a new technology stack projected to predict and prevent an additional $1.5MM worth of fraud every month. It was a huge responsibility that overwhelmed me at first, but being thrown in the deep end was perfect for my learning and an environment in which I thrived. In doing so, I learned how to use and implement several new libraries, but more importantly I learned several advanced ML and data science concepts including hyperparameter optimization, feature engineering, and backtesting. Not to mention, I was lucky to have the mentorship of several brilliant software developers to indoctrinate me into the industry, teaching me in various sectors of programming skill, as well as in the day-to-day of responsible and effective software development practices and habits, documentation, and how to work effectively on an Agile Scrum team.


Talking high-level tech stack, the Java-centric code base worked out well with Java being my mother language since the age of 14, and we worked a lot with Maven, Gradle, Spring Boot, Postman and Groovy. The ML side had me use the XGBoost, XGBoost4J, and TensorFlow libraries, ONNX packaging and formatting, and touching on some Python. The DB and payload work had lots of SQL and querying. And as a developer, I got started working professionally with Git and Bash, as well as Jira and Confluence. I'm quite lucky to have gotten the chance to learn to use so much new technology, and there's even more to list given a new resource, tool or entire tech stack for almost every new task. Thanks to the greatest supervisor, Jason He, it never got monotonous or repetitive. Yet another reason why I spoke so highly of the experience to many of you.



As most of you know, I'm a huge math guy - I'm drawn to anything that lets me use my quantitative skillset, using logic, algorithmic problem solving, optimization, spatial thinking,

analysis - it's both what makes my brain tick and the skill I'm most proud of. I went from growing up on math contests to coding, statistical programming, data science and machine learning, and now I'm in and around a quantitative development obsession combined with some

ML and AI interest. So, having almost no ML experience

going into the term, the opportunity was perfect for me to pick up a skill that I felt would align so well with my quantitative abilities and interest, and that I was so excited to learn. Starting off with hours of introductory ML lessons from Jason once again, the project kicked off 4 months of intense ML exploration and individual learning, both for Interac and on my own. From there, I went on to compete in several ML, AI, and data-based hackathons, explore the ML side of quantitative finance and algorithmic trading, and begin competitively trading both with and without ML. More details about all of this to come in a future post, along with hopefully a very cool quantitative fall co-op announcement despite this brutal internship market.



Aside from the main project, I had a ton of other, very diverse tasks throughout my internship, mostly working to support the release of new and exciting innovation in payment services. I worked with the bulk payload processing system and had the chance to enhance it for some cool new development for Canada's payment services space,

some data archiving and DB manipulation work, and a bunch more. It was quite interesting to work with something I use constantly in my day-to-day life in debit and e-transfer.



Wanting to diversify my knowledge, I had the chance to learn about the Product Management side of things thanks to mentorship from Sarita, especially about the fintech sector and the industry that is financial and payment services. I also got the chance to learn about Data Science & Analytics from shadowing and working with our incredible head of Analytics Engineering, Omar Ghaleb. A great introduction into a more me-aligned side of what the company does, I loved my time in software but it would be really cool to come back to Interac as a DS or analytics intern.


I know I can't get everyone, but there's a few people who had big impacts on me throughout my term. First of all, the senior interns - especially Divyanshu Singh and Justin Yeung, two brilliant senior software interns who taught me a lot. Divyanshu especially, for getting his return offer as a full-timer that we all saw coming and was very well deserved. And of course, the most supportive and helpful bosses, Jason He, Priya Khanna, and Florin Munteanu. You all consistently showed me genuine care not just in my professional development, which has been invaluable in itself, but in me as an individual. Having superiors and a community who really expressed interest in and cared about my learning and development meant the world to me and helped me in so many ways.



Being a developer did have one downside - remote work. Everyone has their preferences, but I found that I couldn't learn the same way remotely. It was just the dev team though, and the office was usually packed with the other teams, and the other interns. Being someone who loves being around people 24/7, I was happy to work out of there whenever I could, getting the chance to meet and learn from an incredible, warm and supportive community of people. A special and specific shoutout for the warm welcome and forever smiling faces of Prabhjit,

Marco, Marvie, and Matt! Some of my fondest memories over the term came from random work events and parties, volunteer week, and finally getting to meet the team after months of working together remotely.



My first internship has been such a success, I could not be happier with how the term played out in my personal and professional development, as well as how much I enjoyed it. I can't wait for what it's store over the fall co-op term, and the next 4 after that.



Also, I've really enjoyed writing this! Getting it down on paper has made me really excited for what's to come and rooted me in my interests, aspirations, and next steps. Along with some great reminiscing and compiling of what I've learned. Next I'll get around to running some interviews and showcasing some new and exciting innovation, sharing my thoughts, opinions, and learnings on the world around me, but I'll be glad to continue writing about my experience both in the professional world and out as I jump from dev into the world of quantitative finance, machine learning, and AI. Until next time!

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