What we do

We learn predictive models of price in financial data streams.
We build very high-performance, automated trading systems that house these predictive models.
We operate these trading systems in U.S. stock markets, where we compete with other
market makers for each trade, narrowing spreads and dampening volatility.

Who we are

We are 17 computer scientists, engineers, and mathematicians, mostly PhDs, most
with roots at Bell / AT&T Laboratories. None of us has a background in banking or trading.
Founded in 2007, we have one team at one site a half hour outside NYC.

Why we love it here

  • Our machine learning and performance problems are exceptionally difficult. We think very hard every day.
  • Our software is clean. We keep our coding teams small and refactor frequently.
  • We adhere to an ambitious set of values.
  • We heavily invest in our research infrastructure.
  • Daily trading feedback is exhilarating.
  • This is a high-tech pure-play. We have no Sales, Biz Dev, Marketing, Finance, or HR. We seek no investment or funding.
  • Remuneration is superb. Everyone earns a share of our profits.
  • We work hard, eat and drink well, and value our families and those of our colleagues.

We're always looking for
top flight people

Data science

We discover predictive signals in financial data streams using machine learning, statistical analysis, visualization, and other quantitative techniques. The streams are large (billions of events per day) and extremely noisy, but yield to sustained analysis coupled with occasional bursts of inspiration.

Building systems

Our C++/Linux systems are distributed and have latency requirements specified in nanoseconds. Our input streams are big and bursty. Safety is paramount. This is not for the faint of heart.