Lenovo is a US$57 billion revenue global technology powerhouse, ranked #248 in the Fortune Global 500, and serving millions of customers every day in 180 markets. Focused on a bold vision to deliver Smarter Technology for All, Lenovo has built on its success as the world’s largest PC company with a full-stack portfolio of AI-enabled, AI-ready, and AI-optimized devices (PCs, workstations, smartphones, tablets), infrastructure (server, storage, edge, high performance computing and software defined infrastructure), software, solutions, and services. Lenovo’s continued investment in world-changing innovation is building a more equitable, trustworthy, and smarter future for everyone, everywhere. Lenovo is listed on the Hong Kong stock exchange under Lenovo Group Limited (HKSE: 992) (ADR: LNVGY).
This transformation together with Lenovo’s world-changing innovation is building a more inclusive, trustworthy, and smarter future for everyone, everywhere. To find out more visit www.lenovo.com, and read about the latest news via our StoryHub. Description and Requirements
Position Description:
Lenovo is seeking a highly motivated CPQ Process Analyst to join its Global Transformation Organization, supporting enterprise-level transformation around Configure, Price, Quote (CPQ) capabilities. This global role is pivotal in driving process innovation and AI-enabled optimization across Lenovo’s quoting and pricing landscape.
The ideal candidate will combine deep experience with CPQ platforms and ERP integration with a practical understanding of AI/ML technologies, including their use in predictive pricing, intelligent configuration, and quote automation. This role sits at the intersection of business transformation, technology enablement, and AI strategy execution.
You’ll work cross-functionally with Sales Operations, Product, Finance, IT, and Data Science teams to reimagine quoting experiences through smart workflows and data-driven insights.
Key Responsibilities:
Lead CPQ Process Analysis & Design:Analyze and redesign CPQ processes to improve efficiency, scalability, and business value. Incorporate AI-driven capabilities such as guided selling, dynamic discounting, and predictive quote scoring.
AI Integration & Innovation:Partner with internal data science and AI teams to implement models that support use cases like intelligent configuration, real-time pricing optimization, and workflow automation. Evaluate where GenAI or traditional ML can best be applied within quoting and approval processes.
Cross-Functional Collaboration:Work across Sales, Finance, Product, and IT teams to align CPQ capabilities with business needs. Develop solution blueprints and future-state roadmaps that leverage AI where feasible.
Platform Evaluation & Optimization:Assess current CPQ platforms and integrations. Recommend upgrades or reconfigurations that enable advanced analytics, machine learning input, and greater automation across the quoting lifecycle.
Data, Analytics, & Reporting Support:Support interim and long-term reporting needs. Help define the right data sources and structure for AI use cases, ensuring high data quality and governance.
Training & Change Management:Help develop and deliver training for end users, emphasizing the value and impact of AI-enhanced quoting tools. Support adoption and continuous improvement.
Preferred Skills (Bonus):
Familiarity with pricing engines, rebate/incentive optimization, and segmentation modeling.Experience with AI or analytics platforms like Databricks, Power BI, Tableau, or similar.Understanding of knowledge graphs or GenAI approaches for product/configuration advisory.Required Qualifications:
Bachelor’s degree in Business, Engineering, Information Systems, or related field; Master’s degree preferred.5+ years of experience in business process analysis or sales operations, with a focus on CPQ.Demonstrated experience with CPQ platforms (e.g., SAP CPQ, PROS, Tacton, Salesforce CPQ).Proven understanding of quoting workflows, product configuration logic, and pricing models.Practical exposure to AI/ML tools or platforms (e.g., Python, SQL, predictive models, recommendation engines, or GenAI capabilities like prompt tuning for CPQ tasks).Experience collaborating with AI/Analytics teams to turn business requirements into machine learning solutions.Strong grasp of Agile/ASAP methodologies and iterative delivery models.Excellent communication, stakeholder management, and analytical thinking. Additional Locations: * Mexico - Distrito Federal - Mexico D.F. * Mexico * Brazil - Distrito Federal * Mexico - Distrito Federal - Mexico D.F.