0x0000-Duty
1）Using the methods of machine learning and deep learning, studies, analyzes and counts the massive multi-modal historical data, and finds the relevant trends and laws.
2）Keep up with the frontier in the field of deep learning algorithms and promote the improvement of the company's existing algorithms.
3）Research on model interpretability.
4）Other work related to quantitative strategy research.
0x0001-Requirement
1）Master degree or above in computer, mathematics and other majors from famous universities at home and abroad, with 0 ~ 3 years of research or project experience related to machine learning or deep learning.
2）Exploration spirit and good hands-on ability, skilled Python or C + + R & D and application experience in Linux environment.
3）Have an in-depth understanding of one or more deep learning frameworks such as TensorFlow, PyTorch, Theano, etc.；
4）Solid foundation of mathematical statistics, ability to quickly read and understand cutting-edge papers in relevant fields at home and abroad .
5）Skillfully use the classical algorithm and network structure of machine learning and deep learning, design the network structure according to the characteristics of financial data, and realize robust and high-precision prediction in the test set.
0x0002-Bonus
1）Working experience in relevant positions in front-line Internet companies, or research experience in relevant artificial intelligence laboratories.
2）MCM, ACM-ICPC or others award.
3）Fund qualification certificate.

0x0000-职责
1）利用机器学习、深度学习的方法对海量多模态历史数据进行研究、分析和统计，从中找到相关的趋势和规律；
2）紧跟深度学习算法领域前沿，推动公司现有算法的改进；
3）模型可解释性研究；
4）其他与量化策略研究相关的工作。
0x0001-要求
1）国内外名校计算机、数学等数理专业硕士及以上学历，有0~3年机器学习/深度学习相关的研究或项目经验；
2）探索精神和良好的动手能力，熟练使用Python，或者Linux环境下的C++研发、应用经验
3）对TensorFlow，PyTorch，Theano等一个或多个深度学习框架有深入理解；
4）扎实的数理统计基础，快速阅读和理解国内外相关领域前沿论文的能力；
5）熟练运用机器学习和深度学习的经典算法和网络结构，可根据金融数据特性设计网络结构，并在测试集方面实现稳健的高精度预测；
0x0002-加分项
1）国内一线互联网公司或者相关人工智能实验室研究经验；
2）MCM、ACM-ICPC等奖项；
3）基金从业资格证