Anson McCade
PhD/Postdoc Quantitative Researcher - New York/Miami/Chicago
Anson McCade, New York, New York, us, 10261
PhD/Postdoc Quantitative Researcher - New York/Miami/Chicago
Base Pay Range
$300,000.00/yr - $350,000.00/yr
Quantitative Researcher – Systematic Strategies
Role Overview My client is a leading global market‑maker who are searching for exceptional 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
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
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
Seniority Level: Not Applicable
Employment Type: Full‑time
Job Function: Finance
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Quantitative Researcher – Systematic Strategies
Role Overview My client is a leading global market‑maker who are searching for exceptional 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
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
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
Seniority Level: Not Applicable
Employment Type: Full‑time
Job Function: Finance
#J-18808-Ljbffr