This job is closed
We regret to inform you that the job you were interested in has been closed. Although this specific position is no longer available, we encourage you to continue exploring other opportunities on our job board.
Trexquant Investment Lp - Stamford, CT
posted about 2 months ago
Full-time - Senior
Stamford, CT
About the position
The Head of LLM Quantitative Strategy Team at Trexquant is responsible for leading a team of researchers to develop and implement advanced machine learning models for trading strategies based on large language models (LLMs). This role requires a deep understanding of LLMs and the ability to apply machine learning methodologies to complex datasets, driving innovation in quantitative finance.
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 into 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 the 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
Benefits
- Competitive salary, plus bonus based on individual and company performance
- Collaborative, casual, and friendly work environment
