Lead/Senior Quantitative Researcher - Fixed Income Analytics
DRW is a principal trading firm, which means no outside investors or third party funds, and we trade for our own account in markets around the world. Our trading is diverse—across asset classes and instruments, using our own models and systems—and it’s this diversification that sets us apart. Founded in 1992 by bringing together technology, research, and risk management to capture trading and investment opportunities, and we still take that approach today. Though we’ve grown to more than 700 exceptional people in six cities around the world, we have the spirit of a start-up and a constant focus on results.
DRW is looking for an exceptional Quantitative Researcher to oversee Fixed Income Analytics. Initial responsibilities will consist of continuing work on a highly robust, modular and well-documented core analytics platform. Further work will involve standardizing and institutionalizing existing tools across regions and then later assisting in the development and construction of new tools. Initially, this team will be primarily focused on fixed income analytics with the possibility of expanding into other asset classes.
To qualify for this role, you:
- have 3+ years experience researching and developing models for pricing interest rate derivatives products such as swaps and options and performing bond relative value analysis
- can demonstrate expertise in stochastic calculus, probability theory, and other related fields of math
- have an advanced degree in a quantitative field such as math, physics, or financial engineering
- have strong communication and collaboration skills with the ability to work within a multi-disciplinary team that includes software engineers, quantitative researchers, and traders.
- have 3+ years experience implementing financial models in C#, C++, Java, or Python.
- experience leading research initiatives/projects with high degrees of autonomy
Bonus points if you have:
- experience training less quantitative personnel in topics such as fixed income analytics
- experience working with large data sets provided in relational or key-value databases.
- created interactive tools built on top of the analytics you’ve provided