AI-Driven Quant Trading Strategy Intern (On-Chain & TradFi)

Blockchain Academics; Australia; Remote; AUD 17,000 - 26,000; Full time

Benefits offered by this job

Remote-first

Mentorship program

Career growth opportunities

Job summary

Binance is seeking a Quantitative Trading Strategy Algorithm Intern to join our AI-driven research team in Australia. You will explore factor discovery, model development, and backtesting within a fast-paced, data-driven environment.

You are a master's or PhD student in a quantitative field, proficient in Python, and eager to apply ML/DL methods to financial time-series data across traditional and on-chain markets. Remote-friendly internship with mentoring and growth opportunities.

Qualifications

• Master's or PhD candidate in a quantitative field with strong programming skills.
• Strong interest in quantitative trading strategies and backtesting workflows.
• Proficient in Python and ML/DL methods for quantitative finance.
• Experience with financial time-series data.
• Understanding of trading mechanisms in traditional or crypto markets.

Responsibilities

• Discover, construct, and validate trading factors from multiple data sources.
• Design and optimize factor prediction models using ML/DL techniques.
• Design, backtest, and validate trading strategies; assist with risk research.
• Build the quantitative trading pipeline from data to backtesting.
• Track frontier AI-driven trading methods across markets and on-chain assets.

Skills

Python

ML/DL

Time-series data

Quantitative trading

Research mindset

Education

Master's or PhD student in quantitative field

Tools

Pandas

NumPy

Backtesting

Job description

Binance is seeking a Quantitative Trading Strategy Algorithm Intern to join our AI-driven research team in Australia. You will explore factor discovery, model development, and backtesting within a fast-paced, data-driven environment.

You are a master's or PhD student in a quantitative field, proficient in Python, and eager to apply ML/DL methods to financial time-series data across traditional and on-chain markets. Remote-friendly internship with mentoring and growth opportunities.