Senior/Junior Machine Learning Quant Researcher

2 months ago


New York, United States Selby Jennings Full time

Company Overview: A leading hedge fund based in New York City, specializing in quantitative investment strategies that combines rigorous quantitative research with advanced technology to capitalize on market opportunities across global financial markets.

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.

Benefits:

  • Competitive compensation package including base salary and performance-based bonuses.
  • Comprehensive benefits package (healthcare, dental, vision, retirement).
  • Opportunity for professional growth and career advancement in a dynamic and intellectually stimulating environment.


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