Own BI analytics for Wealth/Earn and Trading Tools product lines, covering product performance, user growth, engagement, retention, trading activity, AUM, revenue, and other key business metrics.
Analyze the full user lifecycle and product funnel, including acquisition, activation, product adoption, repeat usage, retention, churn, and cross-product conversion, identifying key drivers and growth opportunities.
Conduct deep-dive analyses on Wealth/Earn products, including subscription and redemption flows, AUM growth, yield trends, asset allocation, user segmentation, retention, and product profitability.
Analyze Trading Tools performance, including adoption and usage of products such as Trading Bots, Grid/DCA strategies, Copy Trading, automated trading features, and other trading tools; evaluate their impact on trading frequency, volume, retention, and revenue.
Build user segmentation and behavioral models to identify high-value users, potential adopters, cross-sell opportunities, and churn risks, supporting product targeting and lifecycle management.
Evaluate cross-product user journeys between Wealth/Earn, Spot, Derivatives, and Trading Tools, identifying opportunities to improve asset activation, trading conversion, and overall user value.
Build and maintain dashboards, automated reports, and monitoring frameworks for key product KPIs, enabling product and business teams to quickly identify performance changes and anomalies.
Support product launches, campaigns, feature iterations, and A/B tests through pre-launch sizing, experiment design, performance measurement, and post-launch impact analysis.
Develop and maintain scalable data models, metric frameworks, and ETL pipelines, ensuring consistent definitions and reliable data across Wealth and Trading Tools products.
Monitor data quality and investigate metric discrepancies across product, transaction, asset, and user datasets, working with Data Engineering and Product teams to resolve underlying issues.
Partner closely with Product, Operations, Marketing, Finance, and Data Engineering teams to define business metrics, identify opportunities, and translate analytical findings into actionable product and growth strategies.
Provide data-driven recommendations on product growth, user monetization, asset retention, trading engagement, and product portfolio optimization.
Fluent in English and Mandarin, both written and spoken.
5+ years of experience in Business Intelligence, Data Analytics, Product Analytics, or a related analytical role.
Experience in fintech, financial services, trading platforms, wealth management, brokerage, or digital assets.
Strong proficiency in SQL and at least one analytical programming language such as Python or R.
Hands-on experience with BI and visualization tools such as Tableau, Looker, Power BI, or similar platforms.
Strong understanding of product and user lifecycle analytics, including funnel analysis, activation, retention, churn, cohort analysis, segmentation, and LTV.
Ability to analyze complex financial or trading products and translate product mechanics into measurable KPIs and analytical frameworks.
Strong analytical and problem-solving skills, with the ability to move from data findings to clear business recommendations and product actions.
High attention to detail with a strong commitment to data quality, metric consistency, and analytical accuracy.
Ability to work independently and manage multiple analytical projects in a fast-paced, cross-functional environment.
Comfortable collaborating with stakeholders across different regions and time zones.
Familiarity with crypto financial products, including flexible/fixed Earn, staking, on-chain yield, structured products, or other digital-asset wealth products.
Experience with trading products or trading tools, such as Spot/Derivatives, Trading Bots, Grid Trading, DCA, Copy Trading, algorithmic trading, or automated trading strategies.
Understanding of key trading metrics such as trading volume, frequency, liquidity, fees, PnL, strategy performance, and trader retention.
Experience analyzing cross-product user behavior, particularly the relationship between asset holding, wealth products, and trading activity.
Experience with A/B testing, statistical analysis, forecasting, causal analysis, or machine learning techniques.
Prior experience at a crypto exchange, brokerage, trading platform, fintech company, or digital asset platform is highly preferred.