Trexquant is a systematic hedge fund where we use thousands of statistical algorithms to trade equity and futures markets globally. Starting with many data sets, we develop a large set of features and use various machine learning methods to discover trading signals and effectively combine them into market-neutral portfolios. We are looking for scientists, engineers, economists, and programmers to develop the next generation of machine learning strategies that can accurately predict the future movements of liquid financial assets.
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 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
- Graduate degree (Bachelors, Masters, or PhD) in any STEM discipline from a prestigious institution
- Passion for machine learning and quantitative finance
- Strong problem-solving skills
- Ability to work effectively both as an individual and a team player
- Proficient in programming languages such as Python
- Previous experience in alpha research and the development of trading signals and strategies
- Experience between 1 years to 10 years
- Competitive compensation with bonus tied to the performance of algorithms you develop
- Work in a collaborative and friendly environment, participate in decision-making process for research direction, and have opportunity to lead on new ideas
Trexquant is an Equal Opportunity Employer