Business Transformation Cpq Process Analyst

**General Information**:

- Req #
- WD00086038
- Country/Region:

- Mexico
- State:

- Distrito Federal
- City:

- Mexico D.F.
- Date:

- Friday, August 1, 2025
- Working time:

- Full-time

**Additional Locations**:

- Mexico - Distrito Federal - Mexico D.F.

**Why Work at Lenovo**:

- We are Lenovo. We do what we say. We own what we do. We WOW our customers.

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).

**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.

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.