Phygital Integrated Retail Customer Journey

1. 01

   Process management & E2E Retail Customer Journey Streamlining ‑ Process Lifecycle Management: Lead the closed-loop management of the retail journey—from "Top-level Design and Development" to "Pilot, Rollout, and Optimization." Identify redundancies in existing workflows and streamline

to dealer to enhance operational efficiency. ‑ Phygital Process Re-architecture: Deconstruct traditional sales workflows to seamlessly integrate digital interactions and AI-assisted tools with physical reception logic. Ensure technical solutions are not "add-on tasks" but core elements embedded within the Dealer SOPs to drive efficiency. ‑ Cross-functional Alignment: Manage the coordination and serve as the central hub for business transformation, coordinating Sales, ND, D&C and IT to reassemble fragmented business requirements into high-efficiency standardized processes, ensuring high consistency and scalability across the retail network ‑ Agile Iteration Mechanism: Establish a dynamic update mechanism for the customer journey, ensuring processes can iterate rapidly based on market feedback and specific requirements for new vehicle launches.

2. 02

   Integration of Physical Space & Digital Touchpoints ‑ Experience integration: Coordinate the physical and digital customer journey elements and design to ensure a seamless online/offline, physical/retail customer journey. ‑ Circulation Efficiency Optimization: Coordinate with all retail facing teams to reduce inefficient physical movement through optimized layouts, creating the ideal physical environment for digital tool application and reduce cost of retail.

3. 03

   Change Management & Implementation Drive ‑ Stakeholder Management: Develop and execute change communication strategies tailored for the dealer network. Leverage business data to demonstrate the value of process updates, neutralizing resistance to change and ensuring high adoption rates of new standards. ‑ Performance Monitoring & Feedback: Build dashboards to monitor process execution, utilizing data analytics to pinpoint operational bottlenecks and provide targeted management interventions or tool optimization requirements. ‑ Empowerment Framework Design: Define post-transformation working model and assist in developing corresponding training requirements and guidelines. Main tasks

4. 01

   Scenario Discovery & Demand Mining ‑ Deep-diving into dealer workflows to identify "breakpoints"; conducting "AI-first" business process redesign; defining the product-market fit for internal AI tools.

5. 02

   Product Design & Technical Logic ‑ Writing high-fidelity BRDs; collaborating with algorithm engineers on model selection and fine-tuning strategies; designing frontend AI interaction patterns (UI/UX for AI)

6. 03

   Evaluation & Data Iteration ‑ Establishing the "Core Indicator System" for AI features; analyzing "bad cases" to refine model performance; managing the data-loop from user feedback to model improvement

7. 04

   PMO & Risk Management ‑ Leading the end-to-end delivery cycle; managing development toolkits; ensuring cross-system integration stability and AI safety compliance.

8. 05

   Ecosystem & Industry Research ‑ Tracking industry trends in Generative AI and B2B retail tech to ensure our systems remain at the forefront of the "Intelligent Upgrade" curve. Becoming part of Mercedes-Benz means finding your individual role and workspace to unleash your talents to the fullest. It means becoming your best self in a global automotive company that has the goal to build the most desirable cars in the world. Empowered by visionary colleagues who share the same pioneering spirit. Together for excellence. Education - Bachelor’s or Master’s degree in Data Science, Information Systems or Business Administration - Full proficiency in English & Mandarin, both written and spoken. Experience ‑ Professional Experience: 5+ years in Product Management, with a significant portfolio in B2B SaaS or Enterprise Internal Systems, 2+ years in AI product management ‑ Hands-on experience in deploying Generative AI (LLMs), predictive analytics, or recommendation engines in a production environment. ‑ Deep understanding of the AI stack: Fine-tuning, Prompt Engineering, Vector Databases, and Agentic workflows. ‑ Ability to perform Abstraction & Modeling of complex business logic into standardized system requirements. ‑ Proficiency in data analysis tools (SQL, Python, or Tableau) to drive evidence-based product iterations. ‑ Scenario Discovery: Exceptional ability to "dock" with cross-functional departments (Finance, Logistics, Sales) to uncover hidden pain points. ‑ Stakeholder Navigation: Proven track record of aligning technical algorithm teams with non-technical business leaders. ‑ Resilience & Agility: Comfortable navigating the ambiguity of emerging technologies and pivoting based on rapid prototyping results. Skills - Solid understanding of the automotive retail business and market dynamics ‑ Well-organized to independently identify and raise issues in a timely manner ‑ Excellent communication skills, with the ability to effectively engage with management and collaborate within cross-functional teams ‑ Strong multi-tasking capability with a structured and efficient working style; adaptable to changing environments ‑ Demonstrates strong ownership mindset and willingness to go the extra mile to deliver results ‑ Proficient in MS Office applications (e.g., Excel, PowerPoint, Word) ‑ Fluent in English and Chinese, both written and spoken