Lead Quantitative Strategist for Large Language Models

4 days ago


Stamford, Connecticut, United States Trexquant Investment Full time
About the Role

We are seeking an experienced quantitative strategist to lead our Large Language Model (LLM) research and development efforts at Trexquant Investment. As a key member of our team, you will be responsible for driving the development of advanced machine learning models to create and develop trading strategies.

Key Responsibilities
  • Lead and develop a team of researchers in researching, implementing, and trading profitable LLM-based quantitative strategies.
  • Continuously stay updated on the latest LLM research and integrate it into signal development and our general investment process.
  • Stay abreast of the latest advancements in machine learning, natural language processing, and quantitative finance, and apply cutting-edge techniques to enhance Trexquant's investment capabilities.
  • Identify datasets useful for building LLM trading strategies and build pipelines to feed these data into our research and trading platforms.
  • Conduct research and experimentation to develop novel machine learning models for quantitative trading strategies across various asset classes and time horizons.
  • Work with our development team to improve accuracy, robustness, and speed of our platform in simulating and trading LLM-based strategies.
Requirements
  • Bachelor's, Master's, or Ph.D. degrees in machine learning, Computer Science, statistical modeling, or other related STEM fields.
  • 4+ years of experience in machine learning research and development, with a focus on large language models and high-volume, data-intensive applications.
  • Strong proficiency in programming languages such as Python, and experience with machine learning libraries/frameworks such as TensorFlow, PyTorch, or Hugging Face Transformers.
  • Demonstrated track record of developing and implementing machine learning models in real-world applications, preferably in the context of quantitative trading or algorithmic trading.
  • Experience managing and growing a team of quant researchers.
What We Offer
  • Competitive salary, plus bonus based on individual and company performance.
  • Collaborative, casual, and friendly work environment.


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