Sr. Product Manager, Vehicle Health Insights

We are the movers of the world and the makers of the future. We get up every day, roll up our sleeves and build a better world -- together. At Ford, we’re all a part of something bigger than ourselves. Are you ready to change the way the world moves? 

Launched in 2023, Integrated Services creates and markets new customer experiences by integrating hardware, software and services across Ford Blue, Model e and Ford Pro. These products and services allow Ford's retail and commercial customers to customize their vehicles like never before with OTA (over-the-air)-driven experiences that grow better over time. Ford is developing leadership at the forefront of connected, digital platforms that will revolutionize every aspect of how vehicles function, the way people interact with them, and the value those vehicles provide.

In this position... 

Are you a technically grounded Product Manager passionate about leveraging data to solve complex real-world problems? Do you thrive in challenging cross-functional environments and believe that product quality is paramount?

We are seeking a skilled and resilient Vehicle Health Product Manager to own the strategy, definition, and delivery of actionable vehicle health insights for Ford and Lincoln connected vehicles. In this role, you will bridge the gap between deep technical data analysis, advanced ML models, and tangible customer and business value, focusing relentlessly on the accuracy and trustworthiness of the insights delivered. You will be instrumental in transforming raw vehicle signals into intelligence that proactively enhances vehicle uptime, improves the customer experience, and drives revenue opportunities across retail, commercial fleet, and subscription services.

What you'll do...

• Define & Deliver High-Quality Insights: Own the end-to-end lifecycle for vehicle health insights, from identifying high-impact opportunities to ensuring successful delivery and adoption by customers, dealers, and fleet partners.
• Technical Partnership & Model Guidance: Collaborate deeply with Data Science and Engineering teams, leveraging your strong engineering background in data analytics; your deep technical understanding of data science, data-driven solutions and your in-depth knowledge in vehicle systems and data.
• Establish Benchmarks & Validate Truth: Define rigorous statistical benchmarks to understand normal vs. abnormal vehicle behavior. Establish and enforce robust Ground Truth validation methods, utilizing real-world outcomes to ensure insights accurately reflect vehicle reality.
• Set Quality Standards & Thresholds: Define and enforce strict quality metrics, including acceptable False Positive and False Negative Rates, to ensure insights are trustworthy, minimize false alarms, and do not miss critical issues. Define clear confidence thresholds for when an insight is actionable and ready for customer communication.
• Navigate Cross-Functional Complexity: Drive collaboration and alignment across diverse internal teams. Navigate challenging discussions and build consensus to ensure insights translate into real customer action and business impact.
• Deep Domain Expertise: Apply your in-depth knowledge of vehicle telemetry, specific signals, Diagnostic Trouble Codes (DTCs), and vehicle systems to inform insight development, data validation, and technical discussions.
• Implement Continuous Improvement: Define "litmus tests" for insight quality and readiness. Establish feedback loops from field teams and customers to measure real-world predictive performance and drive continuous model and insight refinement.

You'll have... 

• Bachelor's degree required in Engineering, Data Science, Computer Science, or a related technical field of study.
• 8+ years of experience in technical product management, data-driven product development, vehicle health, telematics, or a related domain.
• Demonstrated experience in Data Analytics and Data Science, with the ability to understand data pipelines, statistical analysis, and data validation techniques.
• Deep technical understanding of Machine Learning models and how they are built, trained, validated, and deployed in production systems. Comfort engaging in technical discussions with data scientists and engineers.
• In-depth knowledge of vehicle telemetry, specific vehicle signals, and Diagnostic Trouble Codes (DTCs).
• Proven ability to define and manage product quality metrics, including False Positive Rate, False Negative Rate, Precision, and Recall, and understand their impact