Trexquant
Trexquant is a systematic hedge fund where we use thousands of statistical algorithms to trade equity markets all over the world. We develop and use machine learning methods to discover trading signals and effectively combine them into market-neutral portfolios. Our firm has grown significantly in recent years. We have increased the breadth of markets in which we participate as well, the number of our data sources and amounts of data we use, and the complexity of our forecasting algorithms.


Data Scientist
As a member of the Data team at Trexquant, 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 Research team to build predictive machine learning models.

If you are interested in working with a variety of interesting data at a growing systematic hedge fund, we invite you to apply for the Alpha Researcher position at cara.chen@trexquant.com.

Offered benefits:
-Competitive compensation with opportunity for outstanding monetary success
-Work in a collaborative and friendly environment, participate in the decision-making process for research direction and have the opportunity to lead on new ideas
-10 days annual leave from the very first year.

Responsibilities:
-Explore and learn about a wide range of data sets that are used to develop signals for systematic quantitative strategies
-Develop a framework to automatically download and monitor hundreds of data sources that are vital to our trading and research
-Create data visualizations to gain insight on large data sets, such as order-by-order tick data, present findings, and results
- Research and implement machine learning techniques to identify patterns in large data sets and create new derived variables

Desired qualifications:
-A degree in a technical discipline (computer science / mathematics / statistics / others)
-Experience with statistical analysis and mining of large data sets
-Knowledge of Linux, Bash, Python, and SQL Database
-Ability to work independently and take projects to completion, ability to quickly learn about new systems, creative thinking and strong attention to detail is critical

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