Junior Quant: AI-Driven Research & Signals

Binance; United States; Híbrido; USD 120 000 - 180 000; Tempo integral

Resumo da oferta

Binance is building a new research function at the intersection of AI and quantitative trading. We are seeking a Junior Quantitative Researcher to be a founding member, working with senior quants, engineers, and traders to design AI-driven workflows that generate alpha signals and understand market microstructure.

This high-ownership role welcomes fresh-PhD candidates and emphasizes hands-on building with AI agents and LLM-based systems, coupled with a genuine interest in financial markets and

Qualificações

• PhD (recently completed or near completion) in a quantitative field (e.g., CS, ML, Physics, Math, OR, EE).
• Strong Python programming skills and experience with modern data/ML stack.
• Hands-on experience building with AI agents and LLM-based systems.
• Solid grounding in statistics, probability, and ML.
• Genuine interest in financial markets and trading.

Responsabilidades

• Signal research and construction across asset classes using statistics, ML, and AI-agent workflows.
• Root cause analysis of model behavior, signal decay, and PnL attribution; build diagnostic tools.
• Study market microstructure, order book dynamics, and execution costs.
• Design and extend internal AI agent infrastructure for research pipelines.
• Collaborate with traders and engineers to turn ideas into live strategies.

Conhecimentos

Python

Machine learning

AI agents

LLM systems

Statistics

Quant research

Formação académica

PhD in quantitative field

Ferramentas

NumPy

Pandas

PyTorch

JAX

Descrição da oferta de emprego

Binance is building a new research function at the intersection of AI and quantitative trading. We are seeking a Junior Quantitative Researcher to be a founding member, working with senior quants, engineers, and traders to design AI-driven workflows that generate alpha signals and understand market microstructure.

This high-ownership role welcomes fresh-PhD candidates and emphasizes hands-on building with AI agents and LLM-based systems, coupled with a genuine interest in financial markets and