Mobility Marketplace – Marketplace Strategy - Data Analyst

The DiDi International Business Group (IBG) Mobility Marketplace is designed to efficiently connect riders and drivers while optimizing the overall user experience. The Marketplace Strategy (MPS) team functions as a centralized strategic hub, working in close partnership with regional operations worldwide to deliver data-driven solutions that accelerate business growth, strengthen user engagement and retention, and enhance marketplace efficiency. Our responsibilities include conducting in-depth analysis of user behavior and supply-demand dynamics to identify systemic areas for optimization. We design and incubate scalable strategies and develop analytical frameworks to address complex, cross-functional challenges. The team also plays a key role in enabling effective collaboration across Operations, Algorithm, Product, and Engineering functions to ensure seamless strategy execution. MPS initiatives span across fundamental marketplace levers—including dynamic pricing, intelligent dispatching, and incentive design—providing both strategic depth and operational exposure in shaping market-level outcomes and competitive positioning.

Responsibilities ：
As a Data Analyst/Scientist focused on the Mobility Marketplace, 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, internships, or full-time roles—in data science, analytics, or business strategy. • 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.