
DWS Enterprise AI Product Manager
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$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.
Description and Requirements
Job Responsibilities:
1. 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.
2. 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.
3. 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.
4. 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 .
5. Innovation Culture: Foster a culture of experimentation and continuous learning, encouraging rapid prototyping and data-driven decision-making
Job Requirements:
1. 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.
2. 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) .
3. 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 .
4. 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.
