At a Glance
- Tasks: Conduct cutting-edge ML research and develop predictive models for live trading.
- Company: Leading global market-maker with a focus on innovation and collaboration.
- Benefits: Competitive salary, discretionary bonus, and opportunities for professional growth.
- Other info: Dynamic work environment with excellent career advancement opportunities.
- Why this job: Join high-impact teams and make a real difference in the financial markets.
- Qualifications: PhD or Postdoc in quantitative fields with strong ML and statistical skills.
The predicted salary is between 63000 - 77000 £ per year.
Location: Paris, Central London, Central – United Kingdom
Type: Permanent
Role Overview:
My client is a leading global market-maker who are searching for exceptional ML Quantitative Researchers to join high-impact teams focused on systematic trading, predictive modelling, and machine learning research. These roles offer the opportunity to work in fast-paced, collaborative environments where research is directly connected to live PnL. Teams vary in focus — from FX-driven research groups to multi-asset portfolio construction and optimization, but all are looking for individuals with Post-Doctoral Research, technical depth, and a passion for markets.
Key Responsibilities as a Quant Researcher:
- Conduct statistical and machine learning research on large, high-dimensional datasets (including alternative data)
- Develop and improve predictive models, trading signals, and systematic strategies
- Backtest and deploy models in live trading environments
- Contribute to portfolio optimization and risk modeling
- Collaborate with engineers and traders to refine models and drive performance
- Continuously iterate based on model behavior, market dynamics, and new data
Ideal Candidate Profile as a Quant Researcher:
- Currently completing or recently completed a PhD or Postdoc in mathematics, statistics, physics, computer science, engineering, or related quantitative fields
- Strong background in statistical modeling, machine learning, and data analysis
- Proficiency in Python and at least one compiled language (e.g., C++)
- Experience working in a data-driven research environment with practical application
- Strong analytical thinking and a track record of solving complex problems
- Excellent communication skills — able to clearly articulate complex ideas
Preferred Experience:
- Exposure to financial markets, portfolio construction, or trading strategy development
- Familiarity with time-series analysis, NLP, or pattern recognition techniques
- Experience with additional tools such as R, MATLAB, or ML frameworks
Additional Achievements:
- Participation or accolades in elite quantitative competitions (e.g., International Mathematical Olympiad, Putnam Competition, ICPC, Kaggle, or other national/international math and coding contests)
- Top academic performance, such as graduating first in class, Dean’s List, or ranked in the top percentile of degree cohort
- Publication record in top-tier journals or conferences (e.g., NeurIPS, ICML, JMLR, etc.)
- Awards, fellowships, or grants recognizing exceptional academic or research performance
PhD employer: ANSON MCCADE
Anson McCade is an exceptional employer that prioritises employee well-being and professional growth, offering a flexible remote working environment in the UK. With a strong focus on security and digital transformation, employees benefit from comprehensive training programmes and clear pathways for career advancement, all while contributing to impactful projects alongside talented teams and senior stakeholders.
