- Joined
- 10/21/24
- Messages
- 6
- Points
- 3
Hi guys, I’m currently working with a Leading ML Fund as they expand their Quant Research team. They’re hiring in Berkeley, New York (a new but growing office), and remotely.
They are one of the top-performing quant firms in the U.S. right now. In May this year, they increased their AUM by $2 billion. Since their founding in 2007, they’ve been applying ML to solve real-world problems in finance -- and their long-term approach is paying off. Truly one of the pioneering firms in the ML Finance space.
This year alone, we’ve helped three researchers join their team, so we’re very familiar with the interview process and can add lots of value to you.
I’d be happy to share more details about the role, team, comp, and the type of work they’re doing.
Requirements
- Background in modern statistical methods and machine learning with a track record as an applied researcher
- Evidence of strong mathematical abilities (e.g., publication record, graduate coursework, or competition placement)
- Interest in software development techniques and willingness to write production level code (Python and/or R preferred)
- Ability to solve large-scale computing problems
- Eagerness to work in collaborative and diverse teams
- Interest in financial applications is essential, but prior finance industry experience is
not a pre-requisite
- Ph.D. level coursework is required, and a Ph.D. degree in a relevant field is preferred
They are one of the top-performing quant firms in the U.S. right now. In May this year, they increased their AUM by $2 billion. Since their founding in 2007, they’ve been applying ML to solve real-world problems in finance -- and their long-term approach is paying off. Truly one of the pioneering firms in the ML Finance space.
This year alone, we’ve helped three researchers join their team, so we’re very familiar with the interview process and can add lots of value to you.
I’d be happy to share more details about the role, team, comp, and the type of work they’re doing.
Requirements
- Background in modern statistical methods and machine learning with a track record as an applied researcher
- Evidence of strong mathematical abilities (e.g., publication record, graduate coursework, or competition placement)
- Interest in software development techniques and willingness to write production level code (Python and/or R preferred)
- Ability to solve large-scale computing problems
- Eagerness to work in collaborative and diverse teams
- Interest in financial applications is essential, but prior finance industry experience is
not a pre-requisite
- Ph.D. level coursework is required, and a Ph.D. degree in a relevant field is preferred
