VP Engineering - Data & ML Platforms @ Ford Motor Company
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Overview
The people of Ford Motor Credit Company have a 60-year commitment to helping put people behind the wheels of great Ford and Lincoln vehicles. In this role, the VP Engineering - Data & ML Platforms will lead Ford Credit into the future by driving a digital transformation that enhances customer experience and loyalty, while supporting critical business functions such as loan origination, decisioning, customer analytics, and risk management.
Responsibilities
This role involves hands-on technical leadership and strategic oversight. Key responsibilities include:
- Mentor and inspire a global team of 120+ engineering professionals.
- Oversee large-scale and complex data platform and ML program executions.
- Implement a comprehensive data strategy aligned with business objectives.
- Manage financial and resource allocation for major projects.
- Collaborate with senior business leaders and C-level executives.
- Ensure data quality, governance, and regulatory compliance.
Qualifications
The ideal candidate will possess:
- Deep expertise in data engineering and ML platforms.
- Strong hands-on technical and leadership capabilities.
- Experience with modern data architectures and cloud-native technologies, especially on Google Cloud Platform.
- An ability to translate complex technological issues to clear strategies.
- Knowledge of SAS platforms, microservices, and machine learning algorithms.
Additional Information
This is a full-time on-site executive position based in the United States. Visa sponsorship is not available and candidates must be legally authorized to work in the U.S. Ford Motor Credit Company values diversity and is an Equal Opportunity Employer.
Key skills/competency
- Data Engineering
- Machine Learning
- Cloud Platforms
- Leadership
- Strategy
- Data Governance
- Technical Mentorship
- Financial Management
- Microservices
- Regulatory Compliance
How to Get Hired at Ford Motor Company
🎯 Tips for Getting Hired
- Research Ford Motor Company: Understand company values and recent developments.
- Customize your resume: Highlight data and ML leadership experiences.
- Showcase technical depth: Detail cloud and data engineering skills.
- Prepare for executive interviews: Emphasize strategic impact and mentoring.