[Hiring] Applied Data Scientist @Binance

Role Description

We are seeking an Applied Data Scientist to join our Algorithm team — a hands-on builder at the intersection of LLM systems, agentic AI, and crypto-native intelligence. You will design, build, and improve AI agents that understand markets, reason over on-chain data, and take actions at speed for hundreds of millions of users.

• Design and implement production-grade LLM pipelines powering Binance AI Products and next-generation agentic trading features.
• Continuously improve agent capabilities in understanding, reasoning, tool selection, and action execution.
• Build and maintain evaluation frameworks for reasoning model outputs in crypto contexts.
• Apply test-time scaling techniques to push agent reasoning quality in ambiguous, fast-moving market conditions.
• Architect AI system components with rigorous attention to inference latency, throughput, and cost efficiency.
• Integrate on-chain data sources, wallet intelligence, and crypto market signals into LLM-powered analytical pipelines.
• Partner with research scientists to translate experimental findings into production-grade agentic solutions.

Qualifications

• Bachelor's or Master's degree in Computer Science, Electrical Engineering, Statistics, Mathematics, or related technical field.
• 0–5 years of industry or research experience in applied ML or AI engineering.
• Strong Python programming skills; demonstrated comfort with vibe coding.
• Demonstrated hands-on experience with LLMs — prompt engineering, post-training, or end-to-end LLM application development.
• Familiarity with multi-agent system design.
• Strong analytical thinking and problem decomposition; comfortable operating under ambiguity in fast-moving environments.

Benefits

• Shape the future of finance.
• Collaborate with world-class talent in a user-centric global organization with a flat structure.
• Tackle challenging projects in a fast-paced and innovative environment with autonomy.
• Thrive in a results-driven workplace with opportunities for career growth and continuous learning.
• Competitive salary and company benefits.
• Remote-first, work-from-home arrangement (may vary depending on the nature of the role and team).