ML-Centric Research-Driven Investment Firm
Machine Learning Research
New York | Berkeley | Remote (U.S.)
Member & Senior Member of Research Staff
Sartre Group is advising a technology-centric, machine learning–driven investment firm on the continued growth of its research organization.
For nearly two decades, this firm has applied state-of-the-art AI and statistical learning techniques to complex, real-world problems in finance. Founded by leading scientists and built around research excellence, it has evolved into a multi-billion-dollar investment platform with ambitious long-term objectives.
This is a research-first environment where machine learning is central to the firm’s identity and decision-making.
The Environment
You will work alongside internationally recognized experts in artificial intelligence and machine learning, as well as experienced finance and technology professionals. Research colleagues have published extensively in leading academic venues, and regular internal forums ensure active engagement with current scientific advances.
The culture is collaborative rather than siloed, grounded in curiosity, creativity, and intellectual honesty. Long-term platform development takes precedence over short-term iteration.
The Role
As a Member or Senior Member of Research Staff, you will work at the forefront of modern statistical machine learning, addressing enduring challenges in market prediction and portfolio construction.
The work spans the full lifecycle of applied research:
- Leading or contributing to foundational research initiatives
- Working with complex, diverse datasets in high-dimensional settings
- Developing and rapidly iterating predictive models
- Translating research into production systems
- Validating performance in live environments
Despite the complexity of these systems, outcomes are measurable and immediate, creating a tight feedback loop between research and impact.
Senior Members additionally shape research direction, lead major initiatives, and mentor other scientists.
Profile
- PhD in Machine Learning, Statistics, Computer Science, Mathematics, Physics, or a related quantitative field
- Strong grounding in statistical learning, optimization, and modern ML methods
- Experience working with large-scale data and computationally intensive systems
- Production-level programming ability (Python required)
- Empirical, hypothesis-driven mindset
Member level candidates are typically postdoctoral researchers, early-career faculty, or industry ML researchers with demonstrated research depth.
Senior Member level candidates typically bring 5–10+ years of relevant research experience, a track record of leading independent research programs or major technical initiatives, and experience in high-caliber academic labs, advanced industry research groups, or ML-driven technology environments. They demonstrate strong technical judgment, autonomy, and the ability to mentor other researchers.
Prior finance experience is not required. Scientific rigor, originality, and technical depth are paramount.