8:00~9:00: Open the trading strategy and set some operation parameters.

9:00~9:30: Observe the operation of the strategy to ensure that there are no problems.

9:30~ 15:30: Solve the problems of existing strategies, study new strategies and test new ideas.

15:30~ 17:00: analyze the transaction records and determine the trading plan for the next day.

17:00~ 18:00: Exercise

Job responsibilities:

Analyze the data of financial markets (futures, stocks, etc.). ) look for available opportunities; Develop and maintain quantitative trading strategies; Provide corresponding technical support for machine learning/data mining;

Job requirements:

1. Proficient in computer programming and at least one programming language, python is preferred;

Science and engineering background, good knowledge in mathematical statistics and data mining, familiar with machine learning methods (analyzing scientific problems and corresponding data, establishing models and methods, verifying models and methods, applying models and methods and analyzing results, improving models and methods);

Have experience in processing and analyzing a large number of data, and be able to skillfully select and apply data mining and machine learning methods to solve practical problems in scientific research and work; Good self-study and fast learning ability, love work, like the financial industry; At least two years laboratory research experience or R&D experience is preferred;

Extended data

Quantitative trading refers to the use of advanced mathematical models instead of manual subjective judgment, and the use of computer technology to select a variety of "high probability" events that can bring excess returns from huge historical data to formulate strategies.

It greatly reduces the influence of investors' emotional fluctuation and avoids making irrational investment decisions under extremely fanatical or pessimistic market conditions.

References:

Baidu Encyclopedia-Introduction to Quantitative Trading