About this role
About Us
As a Data Scientist, you will be responsible for the overall planning and development of the company-wide data tracking (event instrumentation) system and the scientific experimentation system (A/B Testing), supporting data-driven growth and evidence-based decision-making across the business.
Responsibilities
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Planning and implementation of a full-funnel data tracking system for financial services: Develop a deep understanding of the securities business, and take ownership of the overall planning and standardization of the company-wide, cross-platform (App/Web/PC desktop) full-funnel data tracking system. Establish unified tracking specifications, schema standards, and metadata management solutions, and build a highly available data governance framework. Set up financial-grade data quality monitoring mechanisms, and streamline the automated pipeline from collection to activation, ensuring data meets financial compliance and high-accuracy requirements.
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Overall planning and development of a financial-grade data science experimentation system (A/B Testing): Lead the overall design and methodology development of the company-wide experimentation system (A/B Testing Platform), and plan and drive upgrades to the platform's underlying framework. Collaborate with business lines to build scientific experiment evaluation metric systems, and drive the standardized adoption of experimentation methodologies across diverse scenarios including trading, market data, wealth management, and marketing.
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Advancing data-driven and evidence-based decision-making: Leveraging the tracking system and experiment evaluation framework, promote the adoption of a data-driven culture and methodology at the company level, and provide systematic, science-based decision support for product iteration and operational strategies.
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Requirements**
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Academic background: Bachelor's degree or above in Statistics, Data Science, Computer Science, Applied Mathematics, Econometrics, or a related field.
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Strong theoretical foundation in statistics and experimentation: Exceptionally solid grounding in statistical inference, with a deep understanding of the underlying principles of A/B testing and statistical methods (e.g., hypothesis testing, confidence intervals, variance reduction). Familiarity with causal inference methods (PSM, DiD, Uplift Modeling, etc.) and their application logic in long-horizon or non-randomized intervention scenarios; ability to build systematic analytical frameworks.
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Technical and data capabilities: Proficiency in SQL, with the ability to efficiently process massive, high-frequency behavioral data and trading logs. Proficiency in Python or R for statistical modeling, simulation, and automated analysis scripting.
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Business acumen and systems thinking: Strong interest in and foundational understanding of securities trading, wealth management, or internet finance. Excellent abstraction skills and a holistic perspective, with a talent for distilling complex business scenarios into standardized systems.
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Soft skills: Excellent cross-team communication and project-driving capabilities, with the ability to collaborate effectively with product, engineering, and compliance teams to drive solutions to delivery. Strong self-motivation and resilience under pressure, combined with business and data sensitivity, and the ability to deliver consistently amid concurrent multitasking.
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Excellent English & Chinese listening, speaking, reading, and writing skills; ability to read English technical documentation and to communicate with external vendors in English for day-to-day and technical coordination.
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*Open to candidates graduating between January 2026 and August 2027.