As the scale of accessible knowledge grows exponentially, there is untapped gold in the dry reports of day-to-day business, in the interconnected relationships of people and institutions, and in the “information exhaust” of lives lived online. Algorithms alone cannot untangle these threads of semi-structured data, and the brilliant lone-investor cannot master all the details.

We seek opportunity in the middle path of using advanced machine learning on complex data, guided by the domain-knowledge of world-class experts and always backed up by science.

Rather than playing the zero-sum quant race of refining and speeding up trading models, we use deep-analysis of big-data to build new approaches for investing. We take ideas, wring information out of them as efficiently as possible, and keep moving ahead - nimble, pragmatic and always focused on alpha.

We use tools and systems to solve problems as required - we work with varied partners who provide information that can range over unique alternative data, novel analysis of mainstream data, or common data supplied with unusual depth, thoroughness, or history.

We are specifically interested in analysis tools that can extract knowledge from text or semi-structured inputs, can map connections between disparate ideas, or can help winnow out signal from the terabytes of noise.

Other opportunities, that can defy the categories of what we are already looking for and expand our horizons, are also always welcome.