Junior Quantitative Researcher (Fresh STEM PhD graduates are welcome)
TLDR
Contribute to groundbreaking research by developing AI-driven workflows for quantitative trading strategies in a collaborative environment focused on innovation.
Signal research and construction. Develop, test, and productionize predictive signals across asset classes using a combination of statistical methods, machine learning, and AI agent–driven research workflows. Take ideas from hypothesis through backtest, validation, and deployment.
Root cause analysis (RCA). Investigate model behavior, signal decay, PnL attribution, and unexpected trading outcomes. Build tools — including agentic ones — that accelerate diagnosis and shorten the loop between observation and fix.
Market microstructure research. Study order book dynamics, execution costs, liquidity, and venue behavior to inform both signal design and execution strategy.
AI agent infrastructure for research. Help design and extend internal agentic systems that automate parts of the research pipeline — data exploration, hypothesis generation, backtest configuration, results summarization, and report drafting.
Collaborate broadly. Work closely with traders, engineers, and other researchers to turn ideas into live, monitored strategies.
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PhD (recently completed or near completion) in a quantitative field — e.g., Computer Science, Machine Learning, Statistics, Physics, Mathematics, Electrical Engineering, Operations Research, or a related discipline.
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Strong programming skills in Python; comfortable with the modern data and ML stack (NumPy, pandas, PyTorch or JAX, etc.).
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Hands-on experience building with AI agents and LLM-based systems — for example, tool-using agents, multi-step reasoning pipelines, retrieval systems, or evaluation frameworks. We want to see that you have actually built things, not just read papers.
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Solid grounding in statistics, probability, and machine learning, with the rigor to know when a result is real and when it isn't.
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Genuine interest in financial markets and trading, demonstrable through coursework, personal projects, competitions, internships, or self-directed study.
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Strong written and verbal communication; able to explain technical work clearly to a mixed audience.
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Prior internship or research experience at a hedge fund, prop trading firm, market maker, bank, or fintech.
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Exposure to market microstructure, limit order books, or high-frequency data.
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Experience with backtesting frameworks, time-series analysis, or causal inference.
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Familiarity with low-latency systems, or large-scale data infrastructure.
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Publications, open-source contributions, or trading competition results.
Binance builds a comprehensive blockchain ecosystem centered around the largest cryptocurrency exchange globally, serving over 300 million users across more than 100 countries. We deliver a diverse range of financial services that encompass trading, payments, and institutional offerings, all backed by robust security and transparency. Our mission is to leverage the power of digital assets to enhance financial access and promote the freedom of money worldwide.
- Founded
- Founded 2017
- Employees
- 11-50 employees
- Industry
- Internet Software & Services
- Total raised
- $10M raised