AI-Driven Quant Trading Strategy Intern

Lever, Inc.; Australia; Remote; AUD 39,000 - 52,000; Part time

Benefits offered by this job

Work-from-home arrangement

Networking opportunities

Job summary

Binance is building an AI-driven trading ecosystem and seeks a Quantitative Trading Strategy Algorithm Intern for its Accelerator Program. The role blends quantitative research with AI to develop factors, predictions, and trading strategies across traditional and on-chain assets.

You will collaborate with researchers, implement backtests, and contribute to a fast-paced research pipeline within a global crypto ecosystem.

Qualifications

• Current Master's or PhD student in a quantitative field with programming skills.
• Strong interest in quantitative trading strategies and backtesting workflows.
• Proficient in Python and familiar with ML/DL in finance.
• Understanding of trading mechanisms and data in at least one market.
• Strong learning ability and initiative in a fast-iterating environment.

Responsibilities

• Discover, construct, and validate trading factors from market, fundamental, and on-chain data.
• Design and optimize factor prediction models using ML/DL to improve signals.
• Design, backtest, and validate trading strategies including risk controls.
• Build the quantitative trading pipeline from data to backtesting.
• Track frontier methods in AI-driven trading across equities and on-chain assets.

Skills

Python

ML/DL for quant

Time-series data handling

Quantitative trading interest

Research mindset

Education

Master's or PhD student in quantitative field

Job description

Binance is building an AI-driven trading ecosystem and seeks a Quantitative Trading Strategy Algorithm Intern for its Accelerator Program. The role blends quantitative research with AI to develop factors, predictions, and trading strategies across traditional and on-chain assets.

You will collaborate with researchers, implement backtests, and contribute to a fast-paced research pipeline within a global crypto ecosystem.