Grasshopper is a quantitative trading technology provider based in Singapore, and is the holding company of Grasshopper Asset Management. Our state-of-the-art technology, built from the ground up in-house, puts us at the forefront of developments in electronic trading. An unbroken record of consistency and profitability is underpinned by firm values of curiosity, empowerment and flexibility.
About Grasshopper Asset Management
Grasshopper Asset Management, a subsidiary of Grasshopper, is a Licensed Fund Management Company (LFMC) regulated by the Monetary Authority of Singapore. With low-latency quantitative strategies, we generate diversified, stable and uncorrelated returns with an unbroken 18 year streak of profitability by maintaining multiple layers of algorithmic and manual risk controls.
About the Role:
We are seeking a highly motivated Quant Researcher to join our growing quant trading team. This is a career-defining opportunity to work closely with experienced traders and quantitative developers, gaining hands-on exposure to real trading systems, market microstructure, and quantitative research workflows whilst using your quantitative and programming skills in order to help design, analyse and refine statistical systematic trading strategies in a fast-paced, data-driven environment.
As a key member of the Trading Team, you'll:
Research and improve existing systematic trading strategies across global equities, futures, or options
Analyse large datasets of market microstructure, order book, and tick data to identify opportunities
Develop, backtest, and optimise predictive models using modern statistical, econometric, and ML techniques
Write software (paired with Senior devs / team lead) to translate research insights into efficient C++ production systems
Evaluate performance, quantitative risk management, and continuously refine existing strategies through data-driven iteration
Contribute to the research infrastructure -- simulation tools, data pipelines, and performance analytics
We'd love for you to have:
4-6 years of programming experience (academic or professional) in C/C++ or Python/R
Basic knowledge of networking and Linux environments is a plus
Basic knowledge of producing reproducible research is a plus
Solid understanding of data structures, algorithms, and software fundamentals; demonstrable ability to turn quant ideas into working codes
Proficiency in Python scientific stack (pandas, numpy, scipy), or clear evidence of experience with statistical/machine learning tech-stack in another programming language that we can reuse/redirect you in python/Cpp
Interests or familiarity with predictive statistics, machine learning, econometrics or time-series analysis
Interests in scientific methods for truth finding/hypothesis testing
No prior experience in finance or trading required, but an interest in the domain and a willingness to learn
Must haves:
Balance of pragmatism with a desire to see things done right and ambition to see new teams succeed and profit-share
Open-minded, able to propose ideas, and provide constructive feedback on others' ideas
Intellectual humility: Ability to reason under uncertainty, form hypotheses, and test them empirically, and accept failure/post mortem
Strong attention to detail and curiosity about how markets work
What we offer:
21 days annual leave
An opportunity to learn from experienced professionals, fostering mentorship opportunities and personal growth
Comprehensive Insurance Package with extended coverage for dependents
Well stocked pantry
Annual Dental & Wellness budget
Gym membership
Competitive compensation
#gam
What you can expect working at Grasshopper:
At Grasshopper, you will be working in a diverse and dynamic environment with a flat hierarchy. With over 100 employees and 15 nationalities working in an open office, communication is essential to performance. To keep our edge as the "small giant" of trading technology, we give employees a high level of autonomy and encourage them to get creative, take risks, make mistakes and learn from them. The sprint is on!
Grasshopper is an equal opportunity employer.
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