Quantitative Researcher (Fresh STEM PhD graduates are welcome)

As a Junior Quantitative Researcher at Binance, you will be a founding member of a new research function at the intersection of artificial intelligence and quantitative trading. You will work alongside senior quants, engineers, and traders to design AI-driven workflows that generate alpha signals, diagnose model and PnL behavior, and deepen understanding of market microstructure. This role is suited to someone genuinely excited about markets with a strong research background and experience building with modern AI tooling, including LLM-based agents. Binance welcomes fresh PhD graduates who can demonstrate research depth and a real interest in trading.

What you'll do

• Develop, test, and productionize predictive signals across asset classes using statistical methods, machine learning, and AI agent-driven research workflows, taking ideas from hypothesis through backtest, validation, and deployment.
• Investigate model behavior, signal decay, PnL attribution, and unexpected trading outcomes by building tools, including agentic ones, that accelerate diagnosis and shorten the loop between observation and fix.
• Study order book dynamics, execution costs, liquidity, and venue behavior to inform both signal design and execution strategy.
• Help design and extend internal agentic systems that automate parts of the research pipeline, such as data exploration, hypothesis generation, backtest configuration, results summarization, and report drafting.
• Collaborate closely with traders, engineers, and other researchers to turn ideas into live, monitored strategies.

What you bring

• A recently completed or near-completion PhD in a quantitative field such as Computer Science, Machine Learning, Statistics, Physics, Mathematics, Electrical Engineering, Operations Research, or a related discipline.
• Strong programming skills in Python and comfort with the modern data and ML stack (NumPy, pandas, PyTorch or JAX, etc.).
• Hands-on experience building with AI agents and LLM-based systems, such as tool-using agents, multi-step reasoning pipelines, retrieval systems, or evaluation frameworks, demonstrated through actual projects rather than papers alone.
• Solid grounding in statistics, probability, and machine learning, with the rigor to distinguish real results from noise.
• Genuine interest in financial markets and trading, demonstrable through coursework, personal projects, competitions, internships, or self-directed study.
• Strong written and verbal communication skills, able to explain technical work clearly to a mixed audience.

Nice to have

• Prior internship or research experience at a hedge fund, prop trading firm, market maker, bank, or fintech.
• Exposure to market microstructure, limit order books, or high-frequency data.
• Experience with backtesting frameworks, time-series analysis, or causal inference.
• Familiarity with low-latency systems or large-scale data infrastructure.
• Publications, open-source contributions, or trading competition results.

What we offer

• Competitive salary and company benefits.
• Work-from-home arrangement (arrangement may vary depending on the work nature of the business team).

About Binance

Binance is a leading global blockchain ecosystem and the world's largest cryptocurrency exchange by trading volume and registered users. Trusted by 300+ million people in 100+ countries, Binance offers trading, finance, education, research, payments, institutional services, Web3 features, and more, built on industry-leading security, user fund transparency, and deep liquidity.