Principal Research Scientist - Machine Learning
Job in
City of Westminster, Central London, Greater London, England, UK
Listed on 2026-07-04
Listing for:
IMC
Full Time
position Listed on 2026-07-04
Job specializations:
-
Research/Development
AI Business & Operations, Data Scientist, Research Scientist
Job Description & How to Apply Below
Responsibilities
- Help define and accelerate the long‑term machine learning research agenda within Systematic Equities.
- Identify emerging research directions, evaluate new developments in machine learning, and translate promising academic advances into practical applications.
- Act as a scientific leader, mentor, and advisor across the research organisation.
- Represent the company externally through participation in leading conferences and engagement with the broader machine learning community.
- Conduct original research and develop proof‑of‑concept solutions where appropriate.
- Advise and mentor quantitative researchers on methodology, experimentation and research direction.
- Help guide future investments in research tooling, infrastructure and compute capabilities.
- PhD in Machine Learning, Computer Science, Statistics, Mathematics, Physics or a related quantitative discipline.
- Outstanding academic credentials and a strong publication record in leading research venues.
- Current or recent experience in a faculty‑equivalent academic or research leadership role such as Assistant Professor, Associate Professor, Professor, Group Leader, Principal Investigator, Senior Postdoctoral Researcher, or Senior Research Scientist.
- Deep expertise in modern machine learning and strong awareness of emerging research trends.
- Experience influencing research direction, mentoring researchers, or leading research initiatives.
- Strong programming skills and experience with modern machine learning frameworks.
- Excellent communication skills and the ability to collaborate across disciplines.
Finance experience is not required.
Benefits- Access to world‑class datasets, significant compute resources and a highly collaborative environment.
- Continued engagement with the academic community through conferences and publication opportunities.
- Competitive compensation that reflects scientific excellence and commercial impact.
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