Data Scientist - Trading insight
BinancePosted 4/14/2025
Data Scientist - Trading insight
Binance
Job Location
Job Summary
We are seeking a Data Scientist - Trading Insight at Binance, a leading global blockchain ecosystem. As a Data Scientist, you will design and optimize quantitative trading strategies using statistical modeling, machine learning, and data-driven insights across digital asset markets. You will analyze large-scale datasets to identify predictive signals and alpha opportunities, build robust backtesting frameworks, and collaborate with developers to integrate predictive models into low-latency trading systems. With a strong background in Python, probability theory, time-series modeling, and optimization, you will contribute to systematic portfolio optimization initiatives and shape the future of the blockchain ecosystem. Binance offers a competitive salary, company benefits, and a work-from-home arrangement. As part of a user-centric global organization with a flat structure, you will have autonomy in an innovative environment and opportunities for career growth and continuous learning.
Job Description
Responsibilities
- Strategy Development:Design and optimize quantitative trading strategies using statistical modeling, machine learning, and data-driven insights across digital asset markets.
- Market Signal Research:Analyze large-scale datasets—including order book, tick-level, on-chain, and macroeconomic data—to identify predictive signals and alpha opportunities.
- Backtesting & Simulation:Build and enhance robust backtesting frameworks to validate trading hypotheses under various market conditions and stress scenarios.
- Execution Optimization:Collaborate with developers to integrate predictive models into low-latency trading systems and continuously improve execution performance.
- Portfolio Analytics:Conduct post-trade analysis, PnL decomposition, and contribute to systematic portfolio optimization initiatives.
Requirements
- Bachelor’s, Master’s, or PhD in Computer Science, Applied Math, Statistics, or related fields.
- 3+ years (mid-level) or 6+ years (senior) of experience in algorithmic or quantitative trading.
- Solid background in Python (NumPy, pandas, scikit-learn, PyTorch) and/or C++ for performance-critical components.
- Experience working with market microstructure data, including order books and tick-level data.
- Strong foundation in probability theory, time-series modeling, and optimization.
- Bonus: Experience with kdb+/q, columnar/time-series databases, or high-frequency trading systems. Bonus: Familiarity with crypto market structure, DEX/CEX dynamics, and derivatives trading.
- Excellent communication and documentation skills; Self-driven, curious, and passionate about building scalable trading systems with impact.
