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Global investment management firm built at the intersection of financial theory and practical application. They strive to deliver superior, long-term results for our clients by seeking to filter out market noise to identify and isolate what matters most, and by developing ideas that stand up to rigorous testing. Underpinning this philosophy is an unrelenting commitment to excellence in technology powering their insights and analysis.
Job Description :
As an Embedded Engineer in Research you will build or extend our:
Global asset signal, data and risk estimation infrastructure incorporating millions of data points
Intuitive research APIs leveraging cloud computing and cutting-edge visualizations
High-performance historical simulation/back testing engine for vetting new alpha strategies
Bespoke technology solutions that satisfy the needs of specific asset classes and research needs
Partner with not only local but also global team of research engineers for successful product delivery
▪ BS/MS/PhD in Computer Science, Computational Finance, Data Science, or related discipline
▪ At least 5 - 8 years of experience as a quantitative developer, preferably in the financial services industry
▪ Outstanding communication, coding, debugging, and analytical skills
▪ Strength in pragmatic design and deploying applications using Linux/Docker/Python
▪ An interest in quantitative finance (no finance / trading experience required)
▪ Experience with Python / NumPy / pandas or similar quantitative stack is a plus
▪ Demonstrated contributions to open-source software is also a plus
▪ An aptitude for mathematics, finance and econometrics is desired.