Head of LLM Quantitative Strategy Team (USA)

Posted 23 Days Ago
Be an Early Applicant
Stamford, CT
Senior level
Machine Learning • Business Intelligence
The Role
The Head of LLM Quantitative Strategy Team will lead a team of researchers to develop machine learning models for trading strategies using large language models. Responsibilities include conducting research, applying machine learning techniques, and enhancing investment capabilities through effective data utilization and teamwork.
Summary Generated by Built In

Description

We are looking for an experienced large language model (LLM) specialist to lead and grow the LLM Quantitative Strategy Team at Trexquant. In this role, you will drive the development of advanced machine learning models to create and develop trading strategies. We are looking for someone who demonstrates deep expertise in large language models and strong ability to apply machine learning methodologies to complex, high-volume datasets.

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 the Trexquant’s investment capabilities.
  • Identify datasets useful for building LLM trading strategies. 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 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

Top Skills

Python
The Company
HQ: Stamford, CT
67 Employees
Hybrid Workplace
Year Founded: 2012

What We Do

Being a quantitative finance firm that uses Machine Learning (ML) to create multi-asset portfolios and seek profit from the market, Trexquant has continuously improved its investment and research platform since starting operations, leveraging new and emerging technologies. Trexquant uses rigorous quantitative methods to create multi-asset portfolios in global markets. To do this, Trexquant develops trading signals using its vast and continuously growing collection of data variables used as inputs for more complex trading models called Strategies. The result is an ever-growing and adapting engine built from thousands of intricate models and tens of thousands of signals, tailor-made with the goal to outperform the market during any condition. Capital is managed across 5,500+ cash equity positions across the United States, Europe, Japan, Australia, and Canada.

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