Machine Learning Quant Researcher

2 months ago


New York, United States Selby Jennings Full time

Job Description: They are seeking both Senior and Junior Machine Learning Quantitative Researchers to join their dynamic team. As a member of their research group, you will collaborate closely with portfolio managers, data scientists, and technologists to develop and implement cutting-edge machine learning models and quantitative trading strategies.


Responsibilities:

  • Research and Development: Conduct research to develop, refine, and implement machine learning models for alpha generation and risk management.
  • Data Analysis: Analyze large datasets to identify patterns, correlations, and predictive signals relevant to financial markets.
  • Model Implementation: Translate research prototypes into production-grade code that can be deployed in live trading environments.
  • Collaboration: Work closely with portfolio managers to integrate quantitative research insights into investment strategies.
  • Optimization: Continuously optimize and enhance existing models to improve performance and efficiency.


Qualifications:

For Senior Researchers:

  • Advanced degree (Ph.D. preferred) in Computer Science, Mathematics, Statistics, Physics, Engineering, or a related quantitative field.
  • Proven track record of developing and deploying machine learning models in a financial or trading environment.
  • Strong programming skills in languages such as Python, R, or C++.
  • Deep understanding of financial markets and quantitative trading strategies.
  • Leadership and mentorship experience is a plus.


For Junior Researchers:

  • Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, Physics, Engineering, or a related quantitative field.
  • Some experience or coursework in machine learning and data analysis.
  • Proficiency in programming languages such as Python, R, or MATLAB.
  • Interest in financial markets and quantitative finance.
  • Strong analytical and problem-solving skills.


Additional Skills:

  • Experience with libraries and frameworks such as TensorFlow, PyTorch, or scikit-learn.
  • Familiarity with big data technologies (e.g., Hadoop, Spark) is a plus.
  • Excellent communication skills and ability to work effectively in a collaborative team environment.



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