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Quantitative Researcher

2 months ago

Manhattan, United States Selby Jennings Full time

Responsibilities:

  • Utilize financial and other data to create or improve predictive models
  • Develop and/or leverage leading-edge statistical and machine-learning models to enhance the research and development systems
  • Create algorithms to monetize the predictive signals.
  • Apply statistical techniques for time-series measurement / estimation and prediction

Further Qualifications:

  • NLP Competence: Deep understanding of Natural Language Processing methods required for analyzing unstructured text data.
  • Large Language Models (LLM): Experience working with LLMs necessary for developing state-of-the-art quant strategies informed by vast amounts of textual information
  • Programming: Strong proficiency in Python needed due to its prevalence in statistical modeling tasks relevant to both signal generation & strategy implementation (must also have working knowledge of SQL and other common data science toolkits such as R and Spark)
  • Strong data science modeling intuition and feature engineering creativity
  • Must have graduate degree in a STEM subject (preferably a PhD)
  • Any specific experience with datatsets such as medical transcripts and broker notes would be a plus but not required
  • Open to consider candidates coming from tech or finance industries