Centaur.ai Investments | ML-driven fundamental investing | Boston (geography flexible)
Background:
-Centaur.ai is an early stage hedge fund being launched by two veteran hedge fund managers with experience at multi-billion dollar funds. We are looking for a world-class ML practitioner, with specific expertise in sequence models, to collaborate with us in building a powerful ML-driven approach to long-term investment management.
-Over the past few months we've developed a hypothesis for how to approach to this problem, which is where we want to start. But importantly, our expectation is to work collaboratively to iterate and build upon this initial hypothesis to create a truly unique model
-The ideal partner is someone who, if there is mutual interest and excitement, would be interested in becoming the co-founding CTO of the fund
Exploratory project scope:
To build conviction in the opportunity and start the development process, we'd like to engage a ML practitioner to help us with the following:
1) As a starting point, build a model similar to the one described in a recent academic paper
2) Work with us to construct an a prototype model that builds upon the approach laid out in this paper
Background:
-Centaur.ai is an early stage hedge fund being launched by two veteran hedge fund managers with experience at multi-billion dollar funds. We are looking for a world-class ML practitioner, with specific expertise in sequence models, to collaborate with us in building a powerful ML-driven approach to long-term investment management.
-Over the past few months we've developed a hypothesis for how to approach to this problem, which is where we want to start. But importantly, our expectation is to work collaboratively to iterate and build upon this initial hypothesis to create a truly unique model
-The ideal partner is someone who, if there is mutual interest and excitement, would be interested in becoming the co-founding CTO of the fund
Exploratory project scope:
To build conviction in the opportunity and start the development process, we'd like to engage a ML practitioner to help us with the following: 1) As a starting point, build a model similar to the one described in a recent academic paper 2) Work with us to construct an a prototype model that builds upon the approach laid out in this paper
Compensation will be cash + equity.
Contact davidlplon@gmail.com to learn more!