Team Overview The International Data Science (DS) team of DiDi’s International Business Group (IBG)** serves as the global analytical engine that powers data-driven decision-making across international mobility markets. As a cross-regional and cross-functional team, we collaborate closely with Product, Algorithm, Engineering, and Operations teams to transform complex marketplace signals into actionable insights, scalable strategies, and intelligent systems that continuously optimize both rider and driver experiences. Our work focuses on understanding and optimizing fundamental marketplace mechanisms—such as dynamic pricing, intelligent dispatching, and incentive design—to maintain balanced supply-demand dynamics and drive sustainable business growth. Within the team, we focus on decision-making support, strategy evaluation, and business impact analysis, ensuring that every strategy is grounded in rigorous data analysis and operationally effective. By bridging quantitative rigor with business intuition, we strive to drive marketplace excellence and innovation across diverse international markets. Responsibilities As a Data Analyst/Scientist within DS, you will drive impact across five core areas: strategy modeling and optimization, marketplace dynamics analysis, experimentation and evaluation, strategy enablement, and cross-functional collaboration. Your mission is to ensure that strategic initiatives are grounded in rigorous data science and continuously advanced through machine learning, behavioral modeling, causal inference, and simulation—while being iteratively refined through real-time feedback loops. You will play a pivotal role in enhancing marketplace efficiency, improving user experience, and delivering scalable business outcomes across diverse city environments. In this capacity, you will partner closely with Algorithm, Operations, Strategy Operation, Product and Engineering teams to inform data-driven decisions, shape long-term strategic direction, and contribute to the design of robust, scalable marketplace frameworks. Strategy Modeling and Optimization • Partner with Strategy Algorithm teams to translate high-level business objectives into well defined, quantifiable modeling problems. • Perform pre-implementation assessments to estimate strategy potential and ROI, providing inputs that guide prioritization and directional focus. • Deliver modeling insights and parameter tuning recommendations to support the development and refinement of key strategic initiatives. • Analyze performance variability across cities and propose localized parameter adjustments to improve strategy adaptability and effectiveness at scale. Marketplace Dynamics Analysis • Analyze regional supply-demand dynamics, user behavior patterns, and marketplace efficiency to uncover structural opportunities for improvement. • Monitor key performance indicators and conduct in-depth diagnostics to identify and explain underlying causes of anomalies or deviations. Experimentation and Impact Evaluation • Design A/B tests and staged rollout experiments to rigorously evaluate the effectiveness. • Leverage causal inference techniques (e.g., Difference-in-Differences, Propensity Score Matching, Regression Discontinuity) to estimate impact in non-experimental settings. • Generate actionable insights and data-driven recommendations to guide decisions. Strategy Enablement and Implementation Support • Support the localized deployment of strategies s across regions, including parameter configuration, performance monitoring, and issue troubleshooting. • Provide support during execution, including caliber alignment and data visualization. Cross-Functional Collaboration and Project Delivery • Partner with Operations, Product, Algorithm, and Strategy Operations teams to deliver comprehensive data support across initiatives. • Synthesize complex analytical findings into clear, actionable insights to align stakeholders and accelerate execution. • Provide e