Staff Data Scientist at Ford Global Career Site

Dearborn, Michigan, United States -

Full Time

Start Date

Immediate

Expiry Date

09 Jan, 26

Salary

0.0

Posted On

11 Oct, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Science, Machine Learning, Deep Learning, Statistical Modeling, Python, SQL, Large Language Models, Data Engineering, MLOps, Containerization, Cloud Platforms, Data Storytelling, Operational Technology, Real-Time Data Streaming, Anomaly Detection, Natural Language Processing, Statistical Analysis

Industry

Motor Vehicle Manufacturing

Description

Collaborate deeply with manufacturing operations, engineering, quality, and supply chain teams to identify high-impact problems solvable through data science and AI. Apply a wide range of data science techniques, including advanced statistical modeling, machine learning, and deep learning, to deliver robust and scalable solutions. Work closely with ML Engineers and Data Engineers to ensure seamless deployment, integration, and monitoring of data science models (including LLMs) into production environments, potentially at the edge. Build strong relationships and influence decision-making through compelling data storytelling and business acumen. Experience with specific industrial data historians (e.g. Ignition). Familiarity with containerization (Docker) and orchestration (Kubernetes) for deploying models at the edge. Publications or presentations in the fields of AI, Data Science, or Smart Manufacturing. Experience with specific industrial data historians (e.g. Ignition). Familiarity with containerization (Docker) and orchestration (Kubernetes) for deploying models at the edge. Publications or presentations in the fields of AI, Data Science, or Smart Manufacturing. Experience with real-time data streaming architectures. Established and active employee resource groups Education: Master's or Ph.D. in Data Science, Computer Science, Engineering, Statistics, or a related quantitative field. Experience: 8+ years of progressive experience in Data Science, with a significant portion in a leadership or lead contributor role. 5+ years of direct experience applying data science within a manufacturing or industrial environment, ideally automotive. Proven hands-on experience with Large Language Models (LLMs), including prompt engineering, fine-tuning, and practical application in real-world scenarios. Demonstrated understanding and experience working with Operational Technology (OT) data infrastructure, including data sources (PLCs, SCADA, MES), industrial protocols (OPC UA, MQTT), and data flow from factory floor to analytical platforms. Technical Expertise: Expert proficiency in Python (Numpy, Pandas, Scikit-learn, TensorFlow/PyTorch) for data manipulation, analysis, and model development. Deep knowledge of LLM architectures and practical application frameworks (e.g., Hugging Face Transformers, LangChain, LlamaIndex). Strong SQL skills for complex data extraction and manipulation. Expertise in various machine learning and deep learning techniques, especially those applicable to time-series data, anomaly detection, and natural language processing. Familiarity with MLOps principles, CI/CD for ML pipelines, and model monitoring in production. Understanding of cloud platforms (GCP) and their relevant data/AI services, particularly for hybrid cloud/edge deployments. Leadership & Soft Skills: Strong strategic thinking and problem-solving abilities, capable of navigating ambiguity and driving results in a complex environment. Excellent verbal and written communication, presentation, and interpersonal skills, with the ability to influence cross-functional teams and senior leadership. A proactive, curious, and results-oriented mindset.

Responsibilities

Collaborate with various teams to identify high-impact problems that can be solved through data science and AI. Apply a range of data science techniques to deliver scalable solutions and ensure seamless deployment of models into production environments.