Jobs Companies Trexquant Investment Quantitative Researcher - Early Career (USA)

Sobre esta vaga de Quantitative Researcher - Early Career (USA) na Trexquant Investment

Trexquant Investment · Presencial · New York, New York, United States

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.

Our Quantitative Researchers are embedded within the following teams:

Alpha Researcher:

As a member of the Alpha Researcher team, 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.

Data Scientist:

As a member of the Data Science team, you will be involved in parsing and analyzing large data sets, working on discovering and obtaining new sources of data and collaborating with the Alpha and Strategy team to build predictive machine learning models.

Strategy Researcher:

As a member of the Strategy team, you will be developing systematic strategies based on a variety of machine learning and statistical methods. The data you train and validate comes from actual market trading

When you apply for a Quantitative Researcher role at Trexquant, we will first assess you on the core skills required for the Quantitative Researcher. During the interview process, we will be able to get to know you better, learn about your strengths and match you to the best research team that closely aligns with your skills and preference.

Your Responsibilities:

  • Design, implement, and optimize various machine learning models aimed at predicting liquid assets using a wide set of financial data and a vast library of trading signals
  • Parse data sets to be used for future alpha(strategy) development
  • Investigate and implement state-of-the-art academic research in the field of quantitative finance
  • Collaborate with experienced and resourceful quantitative researchers to carry out experiments and test hypothesis using simulations

Requirements

  • BS/ MS degree in any stem field
  • Passion for machine learning
  • Fluent with programming languages like Python
  • Strong problem-solving skills
  • Ability to work effectively both as an individual and a team player
  • Knowledge of financial accounting is a plus
  • Background in quantitative finance is a plus but not necessary

Benefits

  • Competitive salary plus bonus bonus based on individual and company performance
  • Collaborative, Casual, and friendly work environment
  • PPO Health, dental and vision insurance premiums fully covered for you and your dependents
  • Pre-tax commuter benefits
  • Weekly company meals
  • Trexquant is an Equal Opportunity Employer

Applications are open for both Stamford and New York City offices, the latter with a planned opening in September 2026.

The base salary for this role is $120,000 to $180,000, 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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Como este salário de Researcher se compara

Esta vaga paga $150,000/yrabaixo da faixa típica para vagas de Researcher.

$123,500 a mediana $187,500 $275,000

Faixa típica $163,500–$262,500/yr, com base em 24 vagas de Researcher comparáveis na JobsRadar (pagamento anualizado em USD). Ver insights salariais de Researcher →

Sobre a Trexquant Investment

Trexquant applies quantitative methods to systematically build optimized global market-neutral equity portfolios in liquid markets. Trading signals (Alphas) are developed from thousands of data variables and extensively tested. Strategies dynamically adjust allocations to Alphas depending on recent performance. Thousands of strategies using tens of thousands of signals currently drive our live production, and our talented team of researchers from some of the best schools in the world inject new ideas into our system on an ongoing basis. Capital is managed across thousands of equity positions in the United States, Europe, Japan, Australia, and Canada.

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