Software Engineer/ Performance Engineer

2 weeks ago


Toronto ON, Canada Boosted.ai Full time

ai is a fintech company headquartered in Toronto, Canada with offices in New York City. We provide AI tools to asset managers to augment their equity capital markets research. Boosted.ai empowers finance professionals to use AI and machine learning to sort through massive amounts of data to find stock opportunities. 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). 
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. 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
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)
~ 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
~ As such, we explicitly seek people that bring diverse life experiences, diverse educational backgrounds, diverse cultures, and diverse work experiences. How many years of related full-time work experience do you have? *



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