Quantitative Finance Software Engineer
Toronto
Boosted.ai
Boosted.ai makes AI software that helps investment managers save time, improve portfolio metrics, and make better decisions.Boosted.ai is a fintech company headquartered in Toronto, Canada with offices in New York City and Nashville. We provide finance-specific AI tools that automate custom research workflows, analyzing data continuously from millions of sources, all tailored to the needs of our investment management clients. We are a well funded, post Series-B company - our lead investors are innovators and disruptors in financial and technology markets, including Spark Capital (Twitter, Slack, Affirm), Ten Coves Capital (Plaid, Sentieo, TouchBistro), Portage Ventures (Wealthsimple, Borrowell, Nesto), and RBC (Royal Bank of Canada).
Position Description
As a Quantitative Finance Software Engineer at Boosted.ai, you will work as a developer to help solve real-world, applied finance problems in code. You will play a key role in expanding and enhancing our core portfolio construction and backtesting system. The ideal candidate has experience working on a team to develop software for large-scale quantitative finance applications. This team member is someone who is motivated, is self-aware, and collaborates well.
Responsibilities
- Work directly with product owners to research and develop portfolio construction techniques that our clients use to tackle complex problems
- Contribute high-quality, production code to the development of internal quant codebases
- Solve analytically challenging problems to drive portfolio performance
- Collaborate with web developers, cloud engineers, and data engineers to integrate our quantitative finance applications into the larger Boosted ecosystem
- Play a part in the shared monitoring, support, and maintenance of existing applications
Requirements
- BS or MS in financial engineering, computer science or engineering
- 2+ years experience as a developer in investment management, banking, or fintech
- 2+ years working in Python with scientific libraries (NumPy, Pandas, SciPy, Scikit-learn)
- Knowledge of the financial markets, portfolio construction, and quantitative approaches
- Understanding of large-scale software code best practices (OOP, design patterns)
- Experience with production software development tools (Git, AWS, Jira, Agile)
- Exposure to traditional statistics, artificial intelligence, and machine learning in finance
- Ability to work in a team environment and communicate effectively with team members, managers, and other colleagues
Diverse Perspectives
We know that innovation thrives on product teams where diverse points of view come together to solve hard problems in ways that are just now possible. As such, we explicitly seek people that bring diverse life experiences, diverse educational backgrounds, diverse cultures, and diverse work experiences. Please be prepared to share with us how your perspective will bring something unique and valuable to our product teams.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Agile AWS Banking Computer Science Engineering Finance FinTech Git Jira Machine Learning NumPy OOP Pandas Python Research Scikit-learn SciPy Spark Statistics
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