Imagine working with cutting-edge machine learning models, crunching high frequency data sets and sparring with exceptional and fun colleagues, all while taking part in scaling our business even further.
Does this sound highly appealing to you? Then you might be our new Senior Quantitative Researcher in the Equity Statistical Arbitrage wing of Alipes Capital!
At Alipes Capital, we have been a market leader in equity and electricity algorithmic trading since starting in 2008.
This position is focused on
In doing so, you will get a chance to tackle a variety of software infrastructure challenges, such as:
You will get instant validation of your work and experience short feedback cycles, where going from inception to deployment can be a matter of hours. There will be no red tape to cut and no sales people to consult. It is pure play.
About the team
We maintain an informal atmosphere where technical discussions are valued, and you are encouraged to take ownership of, and pride in, your work. You will impact the direction of the team, prioritize your work and choose the tools that get the job done.
The Quant team consists of eighteen passionate quantitative researchers covering 6 nationalities, with thirteen PhD’s and five MSc’s with expertise in statistical analysis, mathematical modeling and machine learning. The stat-arb sub-team is a tight group of 3 researchers.
We enjoy collaboration and are always willing to lend a helping hand. We work alongside a team of software engineers and a team of traders that implement and conceive the mathematical models together with us. All team members across the organization write code and drive change and are equally willing to engage on a nitty-gritty technical level as well as discuss the larger strategic level.
About you
Nice to have
What we can offer you
Practicalities
To apply, please send us your CV and a cover letter telling us why you think this role is a great fit for you. If your profile looks like a good match, we will get in touch to coordinate an online technical test as a first step in the interview process.