At IE University, we encourage our students to think outside the box and get involved with extracurricular activities that inspire them and push boundaries. Three students from our Bachelor in Computer Science & Artificial Intelligence recently participated in WorldQuant’s International Quant Championships and made it to the regional finals.
The International Quant Championships bring together students, academics and professionals from all over the world to apply their quantitative skills at the intersection of data and financial markets. Designed and hosted by WorldQuant, teams are tasked with developing and backtesting predictive mathematical models—and this year’s teams had access to robust fields of data and tools, performance dashboards and value-add measures. It is a unique and prestigious opportunity to engage with some of the world’s top talent and for students to demonstrate their own quantitative abilities.
Bachelor in Computer Science & Artificial Intelligence students Rayane Boumediene Mazari, Miranda Drummond and Yousif Alsaffar made it to the regional finals of the international competition. Brought together by their program, they are a true testament to the power of teamwork and effective collaboration.
We sat down with the team to hear about this exciting opportunity and what they learned along the way.
Did you know each other beforehand? Who came up with the idea of participating in the competition and how did you first react to it?
We [Rayane and Yousif] have been in the same computer science and artificial intelligence class for a few years. While we’ve been friends, we’ve also been friendly competitors, frequently going head-to-head in various competitions and datathons organized by IE University. More often than not, we’ve found ourselves in the finals, which always made it exciting. This year was different, though. Miranda, a third-year student from our program, discovered the International Quant Championship and approached us with the idea of teaming up. Given our shared interest in the complexity and vast opportunities within this field, we were immediately enthused about collaborating. It was an easy decision to combine our strengths and compete together.
What were the most significant challenges you encountered during the competition, and how did you overcome them?
The competition was tough, especially with over 30,000 teams from all around the world. One big challenge was diving into a field we weren’t experts in. But we quickly adapted and learned on the go. Using our background in machine learning, we approached problems differently from other teams that took a more theoretical, traditional financial route. This mix of quick learning and our tech knowledge really helped us push through.
What were the key strengths that each team member brought to the table?
Each of us brought unique strengths to the team during the competition. Some members had a deep insight into the financial market, while others excelled at implementing advanced optimization models. What made our team successful was the blend of these skills. Everyone had a vital role in ensuring the team functioned effectively and efficiently.
What valuable lessons or insights did you gain from participating in the International Quant Championships?
Our biggest takeaway from the competition was learning the importance of recognizing our team’s strengths and weaknesses. It’s crucial to differentiate ourselves from the competition and leverage every aspect of the competition’s criteria to our advantage. Simply following the crowd won’t yield top results. Staying updated with the latest technology trends and implementing them can give us a competitive edge. In such a competitive setting, it’s essential to be innovative and stay ahead of the curve.
Can you share how your experience at IE University, studying the Bachelor in Computer Science & Artificial Intelligence, may have contributed to your success in the International Quant Championships?
Certainly! Our time at IE University, especially in the Bachelor in Computer Science & Artificial Intelligence, played a pivotal role in our success at the championships and other competitions. Over three years, we delved deep into AI—covering both fundamental and advanced technologies—and gained hands-on experience with a broad spectrum of its applications. The practical approach at IE University was invaluable. Instead of just grasping theoretical concepts, we were constantly encouraged to learn through coding and real-world applications.
Moreover, IE University emphasized the importance of presenting solutions professionally. This went beyond technical know-how; we honed our skills in conveying our business acumen and professionalism. It’s this blend of technical expertise and professional presentation that became a cornerstone of our success. We didn’t just shine technically but also showcased our deep understanding of business requirements.
Were there specific courses or skills you developed at IE University that you found particularly valuable during the competition?
Absolutely. The Bachelor in Computer Science & Artificial Intelligence was structured in a way that equipped us with the foundational and advanced knowledge required for such rigorous challenges. Notably, the courses centered around AI and machine learning stood out as they made up the core of our learning. These courses sharpened our analytical skills, allowing us to dissect complex problems and craft unique solutions.
Additionally, several courses laid a robust foundation in statistical analysis. This foundation was not only vital for the solutions we constructed but also instrumental in understanding recent research papers, enabling us to replicate and adapt novel methodologies for the competition.
For aspiring students interested in participating in this competition, what advice would you give them?
Taking part in this competition is a unique experience, setting it apart from conventional datathons, largely due to its unique problem structure and the controlled environment in which it operates.
One of the foremost pieces of advice we’d emphasize is the necessity of immersing oneself deeply in machine learning. Having a strong grasp of machine learning tools is essential, but it’s just as vital to couple this knowledge with a comprehensive understanding of the financial market. Together, they provide a formidable foundation for anyone wishing to excel in the competition.
Adaptability plays an indispensable role in navigating the challenges of this competition. For instance, we found ourselves working with vast datasets provided by WorldQuant. Yet, due to ownership rights, we were restricted in terms of how deeply we could analyze this data. Encounters with such constraints demand innovative thinking and the ability to adapt your strategies on the fly.
Our advice to any aspiring participants is to arm yourself with both technical and financial expertise while fostering a mindset that thrives on flexibility and creativity. This combination will undoubtedly equip you to tackle the diverse challenges the competition presents.
Has this experience inspired or motivated any specific area of interest to continue learning or to start your professional career?
Yes, it has. We’ve always been interested in how machine learning can be used with big data in the financial market. This competition gave us a real taste of that. We can definitely see ourselves working in this area in the future because there’s a lot to explore and it offers good challenges.