AI Scientist
- Conduct research in the Machine Learning field to improve multiple aspects of the investment pipeline
- Produce trading or predictive signals using innovative Machine Learning algorithms
- Apply the latest in LLM based agentic technology to develop and test innovative trading signals and algorithms
- Implement signal compression and combination techniques using Machine Learning tools
- Implement state of the art machine learning algorithms
- Design deep learning architectures.
- Develop model frameworks for investment professionals
- Collaborate with portfolio managers and researchers to optimize machine learning algorithms
- Communicate optimally with team members, researchers, and portfolio managers
- PhD degree in a quantitative or highly analytical field (e.g., Computer Science, Physics, Mathematics, Statistics, or a related field)
- 2+ years of research or work experience applying Machine Learning in innovative ways to complex problems
- Graduated at the top of your respective educational program, with excellent problem-solving abilities, insight, and judgment with a strong attention to detail
- Demonstrated ability to program. Strong development skills and proficiency in C++, Python, and PyTorch.
- Demonstrated science aptitude via record of creativity and inventions. Ability to run experiments and perform statistical inference.
- Experience with software development tools and practices, such as version control (e.g., Git), continuous integration, and testing frameworks
- Advanced practitioner-level knowledge of statistical inference, machine learning, software solvers, and/or mathematical optimization
- Strong communication skills; ability to express complex concepts in simple terms
- Core Benefits: Fully paid medical and dental insurance for employees and dependents, flexible spending account, 401k, fully paid parental leave, generous PTO (paid time off) that consists of:
- twenty vacation days that are pro-rated based on the employee’s start date, at an accrual of 1.67 days per month,
- three personal days, and
- ten sick days.
- Perks: Employee discounts for gym memberships, wellness activities, healthy snacks, casual dress code
- Training: learning and development courses, speakers, team-building off-site
- Employee resource groups
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