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Candidate will lead the build-out and enhancement of existing quantitative tools for a mid- and low frequency portfolio, working with discretionary macro specialists in economics, momentum, and flow-based disciplines. An ideal candidate would possess a passion for technology and statistics; have a desire to take ownership of their work; and be able to work both independently and collaboratively to maximize team throughput. Responsibilities include, but are not limited to:
Building high-performance components for both live trading and simulation
Refining, and increasing automation and robustness of the research infrastructure including alpha estimation, risk modelling, and backtesting components
Building an efficient storage and access scheme for data and reference data across price, economic, and big data sets
Researching and implementing performance analytics, including signal performance and post-trade analytics
This is an opportunity to leverage the growth potential of a small but expert team. The role offers the candidate an opportunity to achieve a desired career trajectory based not only on their core expertise but also on their preferred areas of growth.
The position mandates excellent quantitative skills
A Bachelors or Masters in Computer Science or a quantitative discipline
2 years of industry experience in a quantitative business is preferred
Strong programming skills in Python
Programming skills in SQL (MySQL preferred) are a plus, but not required
Web scraping experience (BeautifulSoup, Chromium, etc.)
Candidate must have knowledge and experience with performance trade-offs for common hardware and technology decisions
Ability to develop Excel interface layers for quant models for non-technical members of the team