DWS Enterprise AI Product Manager

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

Lenovo is a US$83 billion revenue global technology powerhouse, ranked #153 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.

Key Responsibilities

Strategy Leadership

• Define the AI Vision: Develop and execute a comprehensive AI roadmap aligned with the leasing business strategy, prioritizing high-impact use cases across the lease lifecycle (origination, underwriting, servicing, collections, asset management) .
• Establish the CoE Framework: Build the governance, operating model, and best practices for AI adoption, including model development standards, ethical AI guidelines, data privacy protocols, and performance measurement frameworks.
• Stakeholder Engagement: Partner with Commercial, Credit, Risk, Operations, and DT leaders to identify pain points and opportunities where AI can drive efficiency, revenue growth, and risk reduction.
  
  

Solution Development

• Credit Risk Intelligence: Lead development of AI/ML models for credit scoring, lease default prediction, and portfolio risk analytics—leveraging both traditional financial data and alternative data sources .
• Process Automation: Deploy NLP and generative AI solutions to automate lease document review, contract analysis, and compliance checking; streamline RFP responses and lease negotiation workflows .
• Commercial Optimization: Build predictive analytics for lease pricing optimization (NPV/NER modeling), tenant retention scoring, and market intelligence—analyzing comparable properties, pricing trends, and competitive positioning .
• Servicing Collections: Implement AI-driven customer service (chatbots, intelligent routing) and collections optimization models to improve recovery rates and customer experience.
  
  

Data Technology

• Data Strategy: Define data requirements, ensure data quality, and establish data pipelines to feed AI models—integrating internal systems (leasing management, CRM, ERP) with external data sources.
• Technology Selection: Evaluate and select AI/ML platforms, MLOps infrastructure, and vendor solutions; oversee the build vs. buy decisions for AI capabilities.
• Model Governance: Establish rigorous validation, monitoring, and retraining protocols to ensure model accuracy, fairness, and regulatory compliance.
  
  

Team Building Culture

• Talent Acquisition: Recruit, mentor, and lead a cross-functional team of data scientists, ML engineers, data analysts, and AI product managers.
• Change Management: Champion AI adoption across the organization, delivering training programs to upskill commercial and operational teams in leveraging AI tools .
  
  

Innovation Culture: Foster a culture of experimentation and continuous learning, encouraging rapid prototyping and data-driven decision-making

Qualifications

Education Experience

• Bachelor's degree in Computer Science, Data Science, Engineering, Finance, or related field; Master's or PhD preferred.
• 10+ years of experience in data science, AI/ML, or analytics leadership roles, with 5+ years specifically in financial services or leasing/finance industries.
• Proven track record of deploying AI/ML solutions in production at scale within regulated financial environments.
  
  

Technical Skills

• Deep expertise in machine learning (supervised/unsupervised learning, deep learning, NLP, time series forecasting) and generative AI applications.
• Proficiency in Python/R, SQL, and cloud AI platforms (AWS SageMaker, Azure ML, GCP Vertex AI).
• Experience with MLOps practices (model CI/CD, monitoring, versioning) and ML frameworks.
• Understanding of leasing economics, credit risk modeling, and financial analytics—including NPV, NER, and cash flow modeling .
• Knowledge of lease accounting standards, regulatory compliance, and data privacy (GDPR, CCPA) .
  
  

Business Leadership Skills

• Strong commercial acumen with ability to translate complex technical concepts into business value propositions for executive stakeholders .
• Experience building and leading high-performing data science teams in fast-paced environments.
• Exceptional communication and influencing skills; ability to drive change across organizational silos.
• Creative problem-solver who can think beyond conventional financial services approaches .
  
  

Key Success Metrics

• Business Impact: Measurable improvements in lease origination velocity, credit loss reduction, portfolio yield optimization, and operational cost savings.
• Model Performance: Accuracy, fairness, and stability of AI models; adherence to governance and compliance standards.
• Adoption Rates: User adoption of AI tools across commercial, credit, and operations teams.
• Innovation Pipeline: Number of new AI use cases identified and piloted annually.
  
  

We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, religion, sexual orientation, gender identity, national origin, status as a veteran, and basis of disability or any federal, state, or local protected class.