数据科学专家

岗位职责 / Responsibilities

Key Responsibilities

• Data Infrastructure & Metric Architecture: Architect and continuously iterate the core business indicator system and foundational data marts for platform services. Drive the design of robust feature libraries and standardized data assets, ensuring high data quality and a "single source of truth" to power global analytics, machine learning models, and business intelligence.
• Domain-Specific Modeling & Problem Solving: Lead quantitative modeling and deep-dive analysis for critical service areas. Design and deploy machine learning and statistical models to optimize ETA/routing accuracy, enhance proactive risk mitigation (Safety), or improve customer issue resolution efficiency.
• LLM Integration & Stakeholder Empowerment: Establish Large Language Models (LLMs) as a horizontal analytical capability within the Data Science team. Develop standardized AI toolchains and methodologies to elevate the team's internal efficiency, while leveraging these advanced capabilities to empower business stakeholders with automated insights, scalable data solutions, and novel strategic levers.
• Experimentation & Causal Inference: Design and evaluate complex A/B tests and utilize causal inference to deeply understand user behavior, measure the true impact of service improvements, and guide strategy iteration.
• Cross-functional Leadership & Productization: Collaborate seamlessly with Product, R&D, Operations, and Algorithm teams across multiple regions to ensure data science solutions are properly engineered, productized, and scaled globally.
• Strategic Roadmap & Mentorship: Actively partner with business leaders to define mid-to-long term roadmaps, precipitate analysis frameworks and feature libraries, and mentor junior data scientists to elevate the team's overall delivery capabilities.

任职要求 / Requirements

Qualifications

• Education: Bachelor’s degree or above in a quantitative discipline (e.g., Statistics, Mathematics, Computer Science, Data Science, Operations Research).
• Experience: 3+ years of full-time working experience in data science, advanced analytics, or algorithm modeling within the Internet industry.
• Domain Expertise: Proven experience in two-sided network platforms (e.g., ride-hailing, food delivery) is highly preferred. Deep familiarity with Trust & Safety, Intelligent Customer Service, or Mapping/Routing (Geospatial) business logic is a strong plus.
• Technical Skills: Deep, hands-on proficiency in complex A/B testing, causal inference, and machine learning. Skilled in SQL and Python (Pandas, NumPy, Scikit-learn) with practical experience deploying LLMs for business optimization.
• Leadership & Business Acumen: Strong business intuition with a track record of proactively translating ambiguous requirements into concrete DS problems. Experience managing complex projects or leading teams (solid or dotted line).
• Language & Culture: Excellent communication skills to navigate fast-paced, cross-functional environments. English must be highly fluent and seamlessly used as a working language. Candidates with MNC, overseas work, or overseas educational backgrounds are strongly preferred.