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- Tasks: Join our quant team to build and maintain analytics tools while learning Python and financial analytics.
- Company: Be part of a leading bank focused on nurturing future talent in quantitative development.
- Benefits: Gain hands-on experience, mentorship, and potential for a long-term role in a dynamic environment.
- Why this job: This internship offers real-world exposure, a learning-first culture, and the chance to work on impactful projects.
- Qualifications: Ideal for students or recent grads in Computer Science, Engineering, or Mathematics with Python skills.
- Other info: Embrace curiosity and clarity; no prior experience needed, just a passion for learning and building.
We are offering a hands-on 6 months internship opportunity for a curious and technically minded individual to learn how modern quantitative tools are built and used in a front-office environment. This role is part of a broader effort to identify and nurture future talent who could grow into permanent roles supporting or developing the bank's analytics and trading infrastructure.
You will join the quant team on a learning journey that blends Python engineering, financial analytics, and delivery tooling. You'll be exposed to real-world front office workflows involving Excel/PyxLL, web dashboards, backend APIs, and CI/CD automation, all under close guidance from experienced developers and quants. This is a learning-first environment designed to give high potential individuals meaningful exposure and help the team assess long-term fit.
What You Will Learn- How quantitative models and tools are delivered to front-office users.
- Principles of clean software design, version control and testing.
- Support the main Quant Developer in building and maintaining analytics tools.
- Contribute to simple tasks in the codebase: wrappers, unit tests, dashboards, automation scripts.
- Take ownership of small prototyping projects with clear goals and feedback loops.
- Participate in internal code reviews and technical discussions.
- Document what you learn; we value curiosity and clarity over prior experience.
- Students or recent graduates in Computer Science, Engineering, Mathematics, or related fields.
- Solid Python fundamentals and interest in applied problem solving.
- Eagerness to learn about finance and real-world software engineering.
- Self-driven, open to feedback, and excited by the idea of building things that matter.
- Interest in Excel automation or dashboard.
- Curiosity about trading, pricing models or risk analytics.
- A practical platform to learn, build and contribute.
- Exposure to how modern quant teams operate inside a front-office setting.
- Mentorship from experienced quants and technologists.
- A potential entry point into a longer-term role within the bank, depending on fit and business need.
Quantitative Developer Intern – Global Market Engineering employer: BMO
Contact Detail:
BMO Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Developer Intern – Global Market Engineering
✨Tip Number 1
Familiarise yourself with Python and its libraries relevant to quantitative finance, such as NumPy and Pandas. This will not only boost your confidence but also demonstrate your commitment to the role during interviews.
✨Tip Number 2
Engage with online communities or forums related to quantitative finance and software development. Networking with professionals in the field can provide insights and potentially lead to referrals for the internship.
✨Tip Number 3
Work on personal projects that involve building simple analytics tools or dashboards. Showcasing these projects in your discussions can highlight your practical skills and eagerness to learn.
✨Tip Number 4
Prepare thoughtful questions about the quant team’s workflows and tools during your interview. This shows your genuine interest in the role and helps you stand out as a candidate who is eager to contribute.
We think you need these skills to ace Quantitative Developer Intern – Global Market Engineering
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant skills and experiences related to Python programming, quantitative analysis, and any projects that demonstrate your problem-solving abilities. Mention any coursework or projects in Computer Science, Engineering, or Mathematics.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the internship and explain why you're interested in quantitative development and finance. Highlight your eagerness to learn and how your background aligns with the role's requirements.
Showcase Your Projects: If you have worked on any relevant projects, especially those involving Python, Excel automation, or dashboards, be sure to include them in your application. Briefly describe your role and the impact of these projects.
Proofread Your Application: Before submitting, carefully proofread your CV and cover letter for any spelling or grammatical errors. A polished application reflects your attention to detail and professionalism.
How to prepare for a job interview at BMO
✨Show Your Curiosity
Demonstrate your eagerness to learn by asking insightful questions about the role and the tools used in quantitative development. This shows that you're not just interested in the position, but also in growing your knowledge in finance and software engineering.
✨Highlight Your Python Skills
Be prepared to discuss your experience with Python, including any projects or coursework that showcase your coding abilities. Mention specific libraries or frameworks you've worked with, especially those relevant to analytics or automation.
✨Discuss Problem-Solving Experiences
Share examples of how you've approached and solved complex problems in your studies or previous projects. This will illustrate your applied problem-solving skills, which are crucial for a role in quantitative development.
✨Emphasise Teamwork and Feedback
Since the role involves collaboration and code reviews, talk about your experiences working in teams and how you handle feedback. Highlight your openness to learning from others and contributing to group discussions.
