In a summer filled with festivals and political headlines, a quieter but no less impressive story unfolded at Carleton University: a group of students took on a real-world financial analytics problem—and delivered outstanding results.
The inaugural MindBridge Data Science Challenge, held in partnership with the Carleton University Institute for Data Science (CUIDS), invited students to build AI models capable of detecting anomalies in financial data. Over eight weeks, participants worked with a modified credit card transaction dataset, applying machine learning techniques to uncover fraud and digit-pattern irregularities.
The competition launched on May 28 with a lecture by Dr. Aras Kayvan, Senior Data Scientist at MindBridge, who introduced students to outlier analysis—a key concept in identifying unusual patterns in large datasets. From there, students were tasked with designing code-based solutions that balanced technical rigor, creativity, and clarity of insight.
Recognizing Excellence in Applied Data Science
After weeks of development and testing, three students emerged at the top of the leaderboard.
First place went to Amin Nabavi, who earned a MacBook Pro and a guaranteed interview for a paid internship at MindBridge. Second place was awarded to Mohammad Reza Zarei, and third to Ahmed Elnimah—both of whom also received tech prizes and internship interviews.
“We were blown away by the talent and thoughtfulness that came through in these submissions,” said Rachel Kirkham, Chief Technology Officer at MindBridge. “This challenge wasn’t just about building good models—it was about understanding the data, spotting real financial risk, and communicating findings clearly and creatively. These students truly rose to the occasion.”
MindBridge, an Ottawa-based leader in AI-powered financial decision intelligence, has built its reputation on helping finance teams analyze 100% of transactions in real time. Their platform is used by auditors, accountants, and risk professionals to detect anomalies and improve decision-making—making them a natural partner for Carleton’s data science program.
From Campus to Career: A Collaborative Success
“This initiative has been a tremendous success for our students,” said Olga Baysal, Director of the Institute for Data Science at Carleton University. “The challenge offered an opportunity to apply data science to an authentic business problem, and the experience of working with industry experts was invaluable. We are proud of the students who participated and especially of those who earned top recognition.”
The judging panel included senior data scientists from MindBridge—Dr. Aras Kayvan and Nima Anvari—as well as Carleton faculty members Prof. Sriram Subramanian and Prof. Sreeraman Rajan. Their combined expertise ensured that submissions were evaluated not only for technical performance, but also for innovation and clarity of communication.
Precision Meets Strategy: A Student’s Perspective
Third-place winner Ahmed Elnimah shared his experience publicly, detailing how he built an end-to-end machine learning pipeline using XGBoost, Isolation Forest, PCA, and handcrafted statistical features. His solution improved precision-recall metrics over the baseline and demonstrated how thoughtful feature engineering can drive real-world impact.
“I didn’t go in as an expert—I built my way into the top 3 by staying curious, intentional, and relentless,” Elnimah wrote in his GitHub submission.
His model focused on detecting rare anomalies—fraudulent transactions (about 0.17%) and digit-pattern irregularities (roughly 0.01%)—that are often missed by surface-level approaches. By integrating smart ensemble logic and leakage-free design, Elnimah’s system delivered measurable improvements in fraud detection performance.
Ottawa’s Growing Role in AI Innovation
The success of the MindBridge Data Science Challenge also reflects a broader trend: Ottawa is steadily carving out a place for itself in the world of artificial intelligence. With homegrown companies like MindBridge pushing the boundaries of financial analytics and institutions like Carleton University producing highly skilled graduates, the city is becoming a serious player in Canada’s tech landscape.
What makes this partnership stand out is its focus on real-world application. Students weren’t just working on theoretical models—they were solving problems that financial professionals face every day. It’s a great example of how universities and industry partners are working together to equip students with the skills and experience needed to thrive in today’s data-driven economy.
MindBridge and Carleton have already confirmed plans to expand the challenge in 2026, offering even more students the chance to apply their skills to meaningful business problems. As initiatives like this continue to grow, Ottawa’s reputation as a hub for AI innovation is likely to grow with it.
Photo: iStock
