Quantitative Researcher
This Chicago-based Fixed Income Market Data provider is looking for a Quantitative Researcher who considers themselves an expert at what they do, who is curious about inefficient markets, who welcomes extremely complex problems, and is serious about quality code and autonomy. They focus on building modern quantitative market data feeds and visualizations for fixed income trading desks, portfolio managers, issuers, and beyond. We regard the data we create as if we were trading it ourselves, meaning detail, demonstrability, and robustness are key in every facet of our business.
Given the team and firm is small, this role comes with a lot of responsibility that will not only provide fulfilling work, but gives you ample opportunity to be heard and learn new technologies as you work directly under the lead quant.
- Build entirely new models and pipelines from scratch
- Modify, test, and validate existing models
- Develop optimization frameworks for existing models
- Contribute to QA testing and distributed computing framework
- Collaborate with other researchers and developers to improve run times and results
- Evaluate new datasets
Skills we are interested in:
- Applied Mathematics / Statistics
- Machine learning / MLOps best practices
- Experience with high-dimension, sparse datasets
- Python / Rust / C++
- AWS (or similar) tools - s3, docker, remote development
- Linux
- Strong analytical abilities and troubleshooting skills
- Ability to work in a team setting
Must have at least a Master's degree in Mathematics or Computer Science.
Must have completed graduate coursework in: Brownian Motion and Stochastic Calculus, Probability and Statistical Physics, and Machine Learning.
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