量化投研研究员-算法与策略方向
Core
Develop quantitative investment strategies for retail investors by combining large language models with traditional quantitative methods, focusing on factor selection, ETF allocation, sector rotation, and timing.
Role type
Senior quantitative research engineer (AI/LLM integration)
Builds
Retail-facing quantitative investment products and data infrastructure
Domain
Financial services / Quantitative trading / Artificial Intelligence
Deliverable
production ML models
Required skills
Quantitative strategy development, Large language model (LLM) integration, Factor modeling, Backtesting frameworks, Financial data engineering, Product thinking, Risk profiling
Preferred skills
Sell-side research experience, Public presentation skills, Cross-functional collaboration
Technologies
LLMs, Quantitative backtesting systems, Financial data pipelines
Responsibilities
Design and develop quantitative strategies for retail users; Build explainable research methodologies and data systems from scratch; Optimize AI product features for information presentation; Implement strategy routing based on user risk preferences; Validate strategy effectiveness through historical backtesting; Provide financial data labeling support to internal teams.