Job Description

This is a technical Individual Contributor (IC) role that requires a deep understanding of the full data science lifecycle. You won't just be building models in a vacuum; you will work cross-functionally with Product Managers, Industrial Designers, and Plant Engineers to ensure your solutions are robust, scalable, and integrated into the physical workflow of our factories. You will be a key player in Ford’s transition to a software-defined manufacturing powerhouse.

• Model Development: Design and implement advanced machine learning models for predictive maintenance, anomaly detection, and computer vision-based quality control.
• End-to-End Pipeline Construction: Architect data pipelines from ingestion (sensor data, PLC logs) to model deployment and monitoring using GCP and Python.
• Statistical Analysis: Apply rigorous statistical methods to identify patterns in manufacturing data that correlate with vehicle quality or equipment downtime.
• Cross-Functional Collaboration: Partner with Product and Engineering teams to translate manufacturing pain points into technical requirements and deliver user-centric data products.
• Technical Leadership: Act as a subject matter expert within ATP, conducting code reviews, mentoring junior scientists, and staying at the forefront of AI/ML research in the industrial space.
• Scalability: Ensure models are optimized for production environments, moving from localized pilots to global plant-wide deployments.

• Data Strategy: Work with data engineering to improve data collection protocols and sensor telemetry quality from the plant floor.