Senior Data Scientist

Ford • Palo Alto, CA

18h • Hybrid

About The Position

Ford is undergoing its most significant transformation in over a century, and our manufacturing plants are at the heart of this evolution. In this role, you will sit within the ATP organization, focusing specifically on the "smart factory" initiative. You will be responsible for developing, deploying, and scaling machine learning models that address critical manufacturing challenges: predictive maintenance for robotics, real-time anomaly detection on the assembly line, and automated quality control.
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.

Requirements

• Education: Requires a bachelor’s or foreign equivalent degree in computer science, information technology or a technology related field
• Master’s degree in Data Science, Computer Science, Statistics, Engineering, or a related quantitative field.
• Experience: 5+ years of professional experience in a Data Science role, with a proven track record of deploying models into production environments.
• Proficiency in Python (R and SQL are also highly valued).
• Expertise in machine learning frameworks: PyTorch, TensorFlow, Scikit-learn, XGBoost, and LightGBM.
• Experience working within Google Cloud Platform (GCP) (Vertex AI, BigQuery, Dataflow).
• Previous experience with time-series analysis, industrial IoT data, or manufacturing quality systems.

Nice To Haves

• Advanced Degree: PhD in a relevant field.
• Deep Learning: Experience with Computer Vision (CNNs) for automated inspection or Transformers for complex sequence modeling in sensor data.
• MLOps: Familiarity with CI/CD for machine learning, containerization (Docker/Kubernetes), and model monitoring tools.
• Communication: Ability to explain complex mathematical concepts to non-technical stakeholders (e.g., plant managers and design leads).
• Problem-Solving: A "product-first" mindset—focusing on the business impact of the model rather than just its accuracy metrics.

Responsibilities

• 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.

Benefits

• Immediate medical, dental, and prescription drug coverage
• Flexible family care, parental leave, new parent ramp-up programs, subsidized back-up child care and more
• Vehicle discount program for employees and family members, and management leases
• Tuition assistance
• Established and active employee resource groups
• Paid time off for individual and team community service
• A generous schedule of paid holidays, including the week between Christmas and New Year’s Day
• Paid time off and the option to purchase additional vacation time.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level