Pioneer Talent Program - Applied Data Scientist
at Binance
Posted 15 hours ago
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**Pioneer Talent Program - Applied Data Scientist**: Join Binance, the world's leading blockchain ecosystem, as an Applied Data Scientist through our Pioneer Talent Program. Key responsibilities include developing and implementing machine learning models, collaborating with cross-functional teams, and generating data-driven insights to inform critical business decisions. Required skills: Python, R, SQL, machine learning frameworks (e.g., TensorFlow, PyTorch), data visualization tools (e.g., Tableau, Matplotlib), and experience with big data processing tools (e.g., Spark, Hadoop). Entry-level candidates with a degree in a relevant field are encouraged to apply.
About the Role
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 — across reasoning models that plan before they act, multi-agent systems that orchestrate complex crypto workflows, and test-time scaling that pushes inference-time intelligence to its limits.
You build for real environments: designing agent architectures, improving performance across quality and latency, developing evaluation methods for open-ended tasks, and turning research ideas into production.
Responsibilities
- Design and implement production-grade LLM pipelines powering Binance AI Products and next-generation agentic trading features — including multi-step reasoning agents, tool-selection frameworks, and autonomous workflow execution across spot, perpetual, and on-chain markets
- Continuously improve agent capabilities in understanding, reasoning, tool selection, and action execution — optimizing simultaneously for intelligence, latency, and reliability under high-frequency trading constraints
- Build and maintain evaluation frameworks for reasoning model outputs in crypto contexts — covering market analysis accuracy, agent decision quality, hallucination detection, and adversarial robustness against prompt injection in financial workflows
- Apply test-time scaling techniques — chain-of-thought, self-consistency, process reward models — 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 — leveraging serving frameworks such as vLLM and TensorRT-LLM — in a zero-downtime, 24/7 trading environment
- Integrate on-chain data sources, wallet intelligence, and crypto market signals into LLM-powered analytical pipelines — building the data layer that makes Binance's agents genuinely crypto-native
- Partner with research scientists to translate experimental findings into production-grade agentic solutions with clear performance benchmarks
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 ; Equally important: demonstrated comfort with vibe coding — using AI-assisted development tools fluidly as core part of your workflow
- Demonstrated hands-on experience with LLMs — prompt engineering, post-training, or end-to-end LLM application development
- Familiarity with multi-agent system design — task decomposition, tool use via MCP, memory management, parallel agent execution, and inter-agent communication
- Strong analytical thinking and problem decomposition; comfortable operating under ambiguity in fast-moving environments
