- 1-5 years of professional software engineering experience in a collaborative environment
- Bachelor's degree or higher in computer science or other quantitative discipline
- Understanding of object oriented programming, design patterns, and data structures
- Experience with software delivery lifecycle and writing production-quality code
- Familiarity with instrument pricing and risk software patterns
- Fluency in C++
- Familiarity in Python
- Experience in Rates and/or Credit products (e.g., bonds and swaps)
- Reasonable quantitative and statistical skills
- Team player with strong pride of ownership
- Detail oriented and quick learner in a fast-paced environment
- Commitment to the highest ethical standards
- London preferred, but open to candidates in other locations
Quant Analytics Developer - London, United Kingdom - Chartermore Partners
Description
Job Description
We are one of the world's premier investment firms. The firm deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources.
Role:
Quantitative developer who will join the Central Research Technology team, which builds strategic solutions for research and live trading of quantitative strategies across multiple frequencies and products. This is a unique opportunity to grow your career with the team while building the next generation of research and quant trading systems for the company.
Role/Responsibilities:
Developing re-usable and performant C++ libraries for macro instrument analytics (FX, Rates, Credit), to be used for research, back-testing, and live trading
Integrating the analytics libraries into the wider python research infrastructure to allow trading teams across the company to use it in their research and trading processes
Working with company Data Services to source market data to fuel real time and historical analytics
Reconciliation of calculations against benchmark sources
Requirements: