Binance is a leading global blockchain ecosystem behind the world’s largest cryptocurrency exchange by trading volume and registered users. We are trusted by over 280 million people in 100+ countries for our industry-leading security, user fund transparency, trading engine speed, deep liquidity, and an unmatched portfolio of digital-asset products. Binance offerings range from trading and finance to education, research, payments, institutional services, Web3 features, and more. We leverage the power of digital assets and blockchain to build an inclusive financial ecosystem to advance the freedom of money and improve financial access for people around the world.

REQUIREMENTS

• 5+ years of experience in data analytics, with deep expertise in statistics, machine learning, and data-driven decision-making.
• Proficient in SQL, Python, Spark, Power BI, and Tableau, capable of delivering end-to-end analytical solutions.
• Hands-on LLM experience in developing Prompt, RAG, Workflows,GenAI,Multimodal AI and Agents, with a strong track record of iterative optimization and performance enhancement.
• Strong AI product mindset,able to translate data insights into intelligent product features and drive innovation.
• Excellent English communication skills, experienced in collaborating across multinational and cross-cultural teams.
• Rich analytical background in Web3 or Internet e-commerce industry and AI bot analysis will be beneficial.

• Conducted data analysis focused on User growth/AI chatbot scenarios.
• Delivered advanced analytics, reporting, and BI applications to support strategic decision-making.
• Supported and prioritized data requests from business stakeholders; interpreted change requirements and assessed their business impact.
• Partnered with cross-functional teams to identify and deliver high-impact analytical use cases.
• Led the implementation of AI (LLM)-based autonomous agents for data analysis, chatbot interaction, and sentiment monitoring.
• Mentored junior analysts in executing complex, data-driven projects under tight timelines.