Quantitative Researcher - Early Career (USA)
About The Position
Trexquant is a systematic hedge fund that utilizes thousands of statistical algorithms to trade global markets in equities and futures. The company focuses on developing advanced machine learning strategies to predict financial asset movements. Quantitative Researchers at Trexquant are integrated into specialized teams: Alpha Researcher (developing market-neutral signals, analyzing data, building predictive models), Data Scientist (parsing data, acquiring new data sources, building machine learning models), and Strategy Researcher (developing systematic strategies using machine learning and statistical methods on market trading data). The company assesses candidates on core Quantitative Researcher skills and then matches them to the most suitable research team based on their strengths and preferences.
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
Nice To Haves
- Knowledge of financial accounting is a plus
- Background in quantitative finance is a plus but not necessary
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
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
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
Education Level
Associate degree
