Overview
In this role, you apply advanced statistical ML to financial market prediction and portfolio optimization, shaping models that drive real trading decisions. You join a collaborative research-centric team at a leading AI-driven asset manager with strong academic ties. You will translate research into production-ready solutions and directly impact billions of dollars in trades. This position offers a chance to work at the intersection of academia and live markets, with opportunities to influence strategy and methodology.
Pay / Benefits
- highly competitive compensation
- comprehensive benefits packages
- technology talks by experts
- daily catered lunches
- modern office
- good work-life balance
Responsibilities
- Develop research innovations and experiments to improve models that govern the investment strategy
- Prepare and analyze new datasets to evaluate predictive efficacy
- Develop, validate, and implement new models into production
- Design experiments to improve simulations and test models in live environments
- Communicate and collaborate with Research Staff and Software Engineers to drive tangible outcomes
- Stay current with the latest academic research to identify novel approaches
Key requirements
- Background in modern statistical methods and machine learning with a track record as an applied researcher
- Strong mathematical abilities evidenced by publications, graduate coursework, or competitions
- Interest in software development and willingness to produce production-level code (Python and/or R)
- Ability to solve large-scale computing problems
- Eagerness to work in collaborative and diverse teams
- Interest in financial applications is essential; prior finance experience not required
- Ph.D. level coursework is required and a Ph.D. degree in a relevant field is preferred
- Collaborative mindset
- Strong communication skills
- Problem-solving and analytical thinking
- Modern statistical methods and machine learning
- Python and/or R production-level coding
- Large-scale computing
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