Quantitative Researcher at Quant Trading Hedge Fund

Domeyard is a hedge fund focused on high frequency trading. We are backed by the CEO of one of the largest quant funds in the world ($55 billion in AUM), the pioneer of China's internet industry, one of the world’s biggest fintech investors, and more.  

We are a flat organization, in which the founders sit next to the interns, and traditional titles don't exist. Our flexible work hours, casual dress code, startup environment (open office with a gaming room, snack pantry, catered food) and generous employee perks (insurance, transportation, phone, health and dental coverage) ensure that you can commit fully to your intellectual interests. We welcome cultural diversity and are able to sponsor H1-B visas. 

We are looking for people who share our passion for science and technology, add a fun-loving character to our team, and inspire each other's growth. We are also looking for potential that we can help nurture, which is why no financial experience is expected. You will be joining as an early team member, influencing the firm's direction, collaborating on existing projects, and leading projects of your own. Feel free to show us any work that demonstrates your interests, e.g. code samples, academic publications, GitHub projects. 

For announcements, events, and the occasional team photo, connect with us on Linkedin.

What you'll be doing:

• Deploying low latency statistical arbitrage and electronic market making strategies at multiple venues.
• Collaborating with developers and other researchers to implement research and trading ideas.
• Performing statistical analysis on large data sets.
• Designing and writing documentation for tools that improve research productivity or trading efficiency.

You must have at least 1 of the following competencies:

• Significant experience with programming in C++.
• Extensive research experience in statistics, optimization, numerical analysis, algorithms signal processing, or a related field.
• Work experience in electronic market making or statistical arbitrage.

In addition, here's some of the qualities that we would value:

• Research experience in any scientific, mathematical or engineering discipline.
• Intense passion for solving quantitative problems.
• Experience using data analysis tools in Python or R.
• Experience with declarative programming (e.g. Haskell, OCaml, SQL).
• Familiarity with LaTeX typesetting.