27届秋招-Data Analyst（国际化Intl DS）

Team Overview The International Data Science (DS) team at DiDi’s International Business Group (IBG) serves as the global analytical and scientific engine driving data-informed decisions across international mobility markets. As a cross-regional and cross-functional team, we partner closely with Product, Algorithm, Engineering, and Operations teams to transform complex data into actionable insights, scalable strategies, and intelligent systems that continuously enhance our user experiences. Our work spans multiple layers — from building and maintaining robust data infrastructure and standardized metrics that ensure data consistency and accessibility, to developing scientific evaluation frameworks that support business decisions enabled by rigorous experimentation, and causal inference modelling. At the business application level, we focus on developing and optimizing core mechanisms of various aspects in mobility business — including marketplace strategies, resources allocation, platform service and user experiences — to improve financial efficiency and drive sustainable growth. As part of the team, you’ll dive deep into decision-making support, strategy evaluation, and business impact analysis, ensuring every strategic choice is grounded in data and delivers real-world results. We bridge quantitative rigor with business intuition to foster innovation, operational excellence, and meaningful impact across DiDi’s global mobility 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 end-to-end analytical solutions for high-priority projects.

Qualifications • Master's degree in Mathematics, Statistics, Computer Science, Data Science, Financial Engineering, Operations Research, or a related quantitative discipline. • Strong analytical foundation with hands-on experience—through academic research or internships is preferred • Proficient in SQL and Python, with the ability to manipulate large-scale datasets and build robust analytical workflows end to end. • Familiarity with machine learning, causal inference techniques (e.g., DiD, PSM, RDD), and optimization methods; practical experience in experimentation is a strong plus. • Strong business acumen and critical thinking, with a proven ability to extract actionable insights from complex data. • Excellent communication skills in both Mandarin and English, with the ability to clearly articulate technical ideas to cross-functional stakeholders. • Proactive, self-driven, and able to thrive in fast-paced, collaborative environments.