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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.
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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.
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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.
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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.
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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.
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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.
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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.
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Support product launches, campaigns, feature iterations, and A/B tests through pre-launch sizing, experiment design, performance measurement, and post-launch impact analysis.
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Develop and maintain scalable data models, metric frameworks, and ETL pipelines, ensuring consistent definitions and reliable data across Wealth and Trading Tools products.
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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.
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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.
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Provide data-driven recommendations on product growth, user monetization, asset retention, trading engagement, and product portfolio optimization.
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Fluent in English and Mandarin, both written and spoken.
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5+ years of experience in Business Intelligence, Data Analytics, Product Analytics, or a related analytical role.
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Experience in fintech, financial services, trading platforms, wealth management, brokerage, or digital assets.
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Strong proficiency in SQL and at least one analytical programming language such as Python or R.
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Hands-on experience with BI and visualization tools such as Tableau, Looker, Power BI, or similar platforms.
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Strong understanding of product and user lifecycle analytics, including funnel analysis, activation, retention, churn, cohort analysis, segmentation, and LTV.
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Ability to analyze complex financial or trading products and translate product mechanics into measurable KPIs and analytical frameworks.
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Strong analytical and problem-solving skills, with the ability to move from data findings to clear business recommendations and product actions.
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High attention to detail with a strong commitment to data quality, metric consistency, and analytical accuracy.
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Ability to work independently and manage multiple analytical projects in a fast-paced, cross-functional environment.
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Comfortable collaborating with stakeholders across different regions and time zones.
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Familiarity with crypto financial products, including flexible/fixed Earn, staking, on-chain yield, structured products, or other digital-asset wealth products.
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Experience with trading products or trading tools, such as Spot/Derivatives, Trading Bots, Grid Trading, DCA, Copy Trading, algorithmic trading, or automated trading strategies.
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Understanding of key trading metrics such as trading volume, frequency, liquidity, fees, PnL, strategy performance, and trader retention.
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Experience analyzing cross-product user behavior, particularly the relationship between asset holding, wealth products, and trading activity.
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Experience with A/B testing, statistical analysis, forecasting, causal analysis, or machine learning techniques.
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Prior experience at a crypto exchange, brokerage, trading platform, fintech company, or digital asset platform is highly preferred.