Quantitative Researcher
Trexquant
Quantitative Researcher
Trexquant
Quantitative trading via ML models
Trexquant Investment · Stamford, United States (Hybrid) · Full-time · Posted 2025-08-29
Workplace: hybrid
Department: Quantitative Research and Machine Learning
Trexquant is a systematic hedge fund where we use thousands of statistical algorithms to trade equity, futures and other markets globally. Starting with many data sets, we develop large sets of features and use various machine learning methods to discover trading signals and effectively combine them into market-neutral portfolios. We are looking for data scientists, physicists, engineers, economists and programmers to develop the next generation of machine learning strategies that can accurately predict the future movements of liquid financial assets.
As a Quantitative Researcher you will be involved in developing market-neutral signals, parsing and analyzing large data sets and collaborating with the Data and Strategy Research team to build a diverse set of predictive models. While we are open to researchers in any asset class we are currently focusing on roles in equities, futures, commodities, and event driven research.
Applications are open for both our Stamford and New York City offices.
The base salary for this role is $130,000 to $200,000, and will be determined based on the candidate’s educational background and professional experience. Base salary is one component of Trexquant’s total compensation package, which may also include a discretionary, performance-based bonus. This position is classified as overtime-exempt.
Trexquant is an Equal Opportunity Employer
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Trexquant is a quantitative finance firm that builds multi-asset portfolios using machine learning. It develops investment and research tools that ingest a wide range of data variables to create complex trading models and strategies, which in turn generate trading signals. These signals guide decisions across global markets. The product works by applying advanced machine learning to large datasets to create predictive models and rule-based strategies, which drive portfolio construction and trading actions through the firm’s platform. Trexquant differentiates itself by emphasizing the breadth of data it uses and the depth of machine-learning driven models to craft multi-asset portfolios, aiming to produce signals that outperform global market conditions. The company’s goal is to generate investment performance that beats benchmarks by using data-driven signals and diversified, multi-asset strategies.
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