Machine Learning Researcher

Key Responsibilities：

• Mine alpha factors and build predictive models via deep learning based on multi-dimensional financial market data.
• Explore signal fusion and strategy ensemble approaches to enhance model robustness and portfolio return characteristics.
• Rapidly prototype, reproduce and optimize state-of-the-art deep learning models with mainstream ML frameworks.
• Stay updated on latest academic and industrial research, conduct ongoing model iteration and performance enhancement.

Qualifications：

• Bachelor’s degree or above from top domestic and international universities, majoring in Computer Science, Mathematics, Statistics, Machine Learning or related quantitative disciplines.
• Strong theoretical foundation in machine learning, proficient in Python and mainstream deep learning frameworks; capable of end-to-end data processing and independent modeling.
• Hands-on research or project experience in time series forecasting, NLP or other deep learning related domains.
• Logical, rigorous mindset with excellent self-learning capability and strong interest in applying ML to quantitative finance.
• Prior internship or working experience in Internet, AI, fintech or quantitative domains.

Preferred Qualifications：

• Kaggle competition awards or first-author publications at top ML conferences (NeurIPS / ICML / ICLR).
• Relevant internship experience in quantitative trading, asset management or financial technology.