Location:
Paris, Central London, Central - United Kingdom
Type:
Permanent
PhD/Postdoc ML Quantitative Researcher
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
