Responsibilities: 1. Data Strategy Development and Execution • Establish and continuously refine the company’s data analytics framework; formulate medium- to long-term data strategies to support key scenarios, including platform growth, product optimization, user behavior insights, and risk monitoring. • Drive data governance, metrics framework development, and data warehouse architecture optimization. 2. Business Analysis and Model Development • Lead behavior data modeling and trend analysis for core segments such as user activity, transactions, market dynamics, liquidity, OTC, and derivatives trading. • Design and implement critical business models, including user lifecycle analysis, KYC behavior flow analysis, asset flow modeling, and anomaly detection for risk control. 3. Team Management and Cross-Functional Collaboration • Manage the data analytics team (including BI specialists and analysts) and define team OKRs and KPIs. • Collaborate closely with product, operations, growth, engineering, risk management, and legal teams to deliver data-driven insights and support. 4. Data Product Enablement • Participate in the development and productization of data visualization tools, metrics platforms, and internal BI solutions. • Partner with engineering teams to advance the data platform and real-time data streaming architecture. 5. Data Culture and Compliance • Foster a company-wide culture of data-driven decision-making. • Ensure data access controls within compliance and governance frameworks. Qualifications: 1. Education and Background • Bachelor’s degree or higher in mathematics, statistics, computer science, financial engineering, or a related field preferred. • Over 10 years of experience in data analysis and at least 4 years of team management experience. 2. Industry Experience • Experience in data-intensive industries such as digital asset exchanges, brokerage firms, or fintech preferred. • Familiarity with blockchain product characteristics and data structures, including derivatives trading, OTC, and wealth management products. 3. Technical Skills • Proficiency in SQL, Python, R, Tableau, Power BI, and other data analysis tools. • Expertise in user behavior modeling, A/B test design, predictive analytics, and machine learning techniques (clustering, classification, regression). • Knowledge of data platforms, data warehousing, and data governance is a plus. 4. Management and Communication Skills • Experience managing cross-regional and multicultural teams. • Strong logical reasoning, business insight, and decision-support capabilities. 5. Language Requirements • Fluent in Chinese and English, with the ability to use both languages for reporting and communication.