Quantitative Researcher - Systematic Credit
At a glance
Mid-level Data Science role at Point72. Chicago · full-time · $150,000–$200,000 base.
dataroles summary, based on the employer's posting.
What you'll do
- Build statistical and structural models to research systematic corporate bond and credit derivatives strategies
- Support the research pipeline by implementing fitting tools, organizing data, and producing alpha, risk and transaction-cost models
- Find and rank promising research ideas and datasets for potential alpha
- Work with portfolio managers, developers and traders to improve the investment process and its infrastructure
What you bring
- A master’s or doctoral degree in a quantitative field such as economics, finance or mathematics
- At least two years developing statistical or fundamental alpha signals and risk factors for credit, equities or options
- Experience researching large datasets and strong Python skills, including data research packages and coding practices
- Knowledge of object-oriented programming and CI/CD, plus clear communication and the ability to own work independently and with a team
Who this fits
This role suits a quantitative researcher who can work independently while collaborating with portfolio managers, developers and traders. The position is based in Chicago.
From the employer
Role
Quantitative Researcher for a new team focused on systematic corporate bond and credit derivatives strategies.
Responsibilities
- Independently conduct quantitative research, adopting a rigorous approach and using statistical and structural models
- Contribute to all aspects of the research and production process, including implementation of fitting tools; data organization; generation of alphas, risk and TC models; P&L attribution, etc.
- Proactively search for and prioritize new ideas and datasets for alpha potential
- Contribute to continuous improvement of the investment process and infrastructure in collaboration with the portfolio managers, developers and traders on the team
Requirements
- PhD or Master’s degree in Economics, Finance, Statistics, Mathematics, Physics, or other quantitative discipline
- 2+ years of experience developing statistical and fundamental alpha signals, risk factors for single name credit, equities, or options. Demonstrated ability to conduct research utilizing large data sets
- Experience with FICC, credit or option pricing models is preferred
- Experience with numerical optimization methods is a plus
- Solid programming skills: understanding of the object-oriented programming and CI/CD framework. Proficiency in Python, including with packages used for data research, best practices of coding style, etc.
- Strong communication skills
- Willingness to take ownership of his/her work, working both independently and within a team
The annual base salary range for this role is $150,000-$200,000 (USD) , which does not include discretionary bonus compensation or our comprehensive benefits package. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things.
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