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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Science Supervisor - **Company:** Ford Motor Company - **Location:** Dearborn, MI, United States - **Experience:** Expert - **Salary:** $115,500.0 - $218,100.0 - **Contract:** Permanent contract - **Skills:** Agile Methodology, Artificial Intelligence, Data Analysis, Artificial Neural Networks, Big Data, BigQuery, CAN Bus, Cloud Computing, Cloud Database, Code Review, Continuous Integration, Data Visualization, Data Flow Control, Data Intelligence, Python (Programming Language), Machine Learning, Natural Language Processing, Scrum Methodology, Tensorflow, Software Deployment, Software Engineering, Software Systems, Web Application Frameworks, Data Processing, Google Cloud, Data Ingestion, Pytorch, Retrieval-Augmented Generation, Deep Learning, Model Validation, Generative AI, Keras, Git, Containerization, AI Platforms, AngularJS, Information Technology, Performance Monitor, Machine Learning Operations, Software Version Control, Data Pipelines, Docker - **Published:** October 2, 2026 - **Apply:** https://www.careerjet.com/job/usdb569fbac3124988e7311e4dfa631928/eaa ## About the Role * Bachelor's or master's degree in Computer Science, Data Science, Engineering, or a related field. * Equivalent relevant experience may be considered. * Ph.D. in Computer Science, Data Science, Engineering, or a related field is preferred., * 5+ years of relevant professional experience in data science, machine learning, software engineering, analytics, or a related technical field. * Demonstrated experience leading or supervising software developers, data scientists, or a multidisciplinary technical team. * Experience delivering data science, AI/ML, analytics, or software products through development, deployment, and ongoing improvement. * Experience planning and prioritizing work, coordinating delivery, and managing team resources. * Experience partnering with product, engineering, quality, or business stakeholders to translate needs into technical solutions. * Experience with agile software development practices, such as Scrum or Kanban. * Strong analytical and problem-solving skills, with the ability to communicate complex technical topics clearly. Required Technical Experience * Knowledge of automotive diagnostics, including DTCs, DIDs, and CAN bus signal data. * Proficiency in Python for data manipulation, analysis, and model development. * Strong understanding of AI and machine learning methods, including deep learning, neural networks, and ensemble methods. * Experience developing and training machine learning models using frameworks such as TensorFlow, Keras, or PyTorch. * Experience designing end-to-end machine learning pipelines for data ingestion, processing, modeling, and deployment. * Proficiency with GCP services relevant to machine learning and analytics, such as AI Platform, BigQuery, Dataflow, or TensorFlow. * Familiarity with cloud-based data storage and processing technologies for large datasets. * Understanding of containerization technologies such as Docker for packaging and deploying software or models. * Experience with Git or similar version-control systems and strong software engineering practices, including testing and code review. Preferred Experience * Experience with Angular or another modern front-end framework for dashboards or data visualization. * Prior experience in the automotive industry, especially in vehicle quality, diagnostics, or connected-vehicle data. * Experience applying anomaly-detection techniques to time-series, sensor, or signal data. * Familiarity with MLOps practices and tools for model deployment, monitoring, and lifecycle management. * Experience with Generative AI, RAG, NLP, or related advanced AI techniques. * Experience leading multidisciplinary teams that combine software engineering and data science., Job Category: Global Data Insight & Analytics Degree Level: Bachelor's Degree or equivalent Job Description: We are seeking a hands-on Data Science Supervisor to lead a team … + 14 hours ago ## Description We are seeking a hands-on Data Science Supervisor to lead a team of software developers and data scientists building diagnostic and quality analytics products for Ford vehicles. In this role, you will guide the team in turning diagnostic trouble codes (DTCs), Data Identifiers (DIDs), and Controller Area Network (CAN) signal data into actionable insights that help identify and resolve vehicle quality issues. This role requires a combination of AI/ML engineering expertise, people leadership, product delivery, and stakeholder partnership. You will guide work across the product lifecycle-from data ingestion and model development to deployment of interactive dashboards backed by scalable Google Cloud Platform (GCP) infrastructure. You will champion agile practices, mentor team members, and partner with product, quality, and engineering stakeholders to deliver useful, reliable analytics products. Data Science, AI & Product Strategy * Guide the design and development of anomaly-detection models using DTCs, DIDs, and CAN signal data to identify emerging vehicle quality issues. * Help shape the team's analytics product roadmap by connecting stakeholder needs, vehicle quality priorities, data insights, and technical opportunities. * Evaluate and integrate Generative AI, retrieval-augmented generation (RAG), natural language processing (NLP), and other emerging capabilities where they can add value. * Drive model validation, performance monitoring, and continuous improvement to support production-grade accuracy and reliability. * Translate vehicle quality and diagnostic challenges into practical data science and software solutions. Platform & Product Delivery * Oversee the design, development, and deployment of Angular-based dashboards that present diagnostic and quality insights to internal stakeholders. * Guide the development of scalable, end-to-end ML pipelines on GCP, including data ingestion, processing, modeling, deployment, and monitoring. * Partner with technical teams to ensure products are reliable, maintainable, secure, and fit for operational use. * Manage team priorities, resources, and delivery timelines in support of the product roadmap. * Identify and address delivery risks, technical dependencies, and opportunities to improve product performance. Team Leadership & Organizational Effectiveness * Lead, coach, and develop a team of software developers and data scientists delivering diagnostics and quality analytics products. * Establish clear team priorities, roles, expectations, and accountability. * Foster a collaborative, inclusive, and high-performing team environment focused on customer value, quality, and continuous improvement. * Support workforce planning, knowledge sharing, technical development, and career growth. * Promote disciplined execution and strong collaboration across software engineering and data science workstreams. Engineering Practices & Continuous Improvement * Champion agile practices, including sprint planning, backlog refinement, and retrospectives. * Establish and reinforce engineering practices such as code review, testing, CI/CD, and version control across data science and AI work. * Support the use of MLOps practices for model deployment, monitoring, and lifecycle management. * Identify opportunities to improve data pipelines, model workflows, software delivery, and operational practices. * Stay current on advances in automotive diagnostics, AI/ML, and cloud technologies, and assess their potential application to team products. Stakeholder Engagement & Communication * Partner with quality, engineering, and product teams to understand business and vehicle quality needs and define effective solutions. * Communicate technical findings, model performance, product roadmaps, risks, and delivery progress to technical and non-technical stakeholders. * Build trusted working relationships across the organization and help align stakeholders on priorities, decisions, and outcomes. ## Related Videos - [How Machine Learning is turning the Automotive Industry upside down](https://www.wearedevelopers.com/videos/61-how-machine-learning-is-turning-the-automotive-industry-upside-down) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Machine learning in the browser with TensorFlowjs](https://www.wearedevelopers.com/videos/155-machine-learning-in-the-browser-with-tensorflowjs) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) - [Overview of Machine Learning in Python](https://www.wearedevelopers.com/videos/840-overview-of-machine-learning-in-python) ## Related Articles - [How software is steering vehicle technology](https://www.wearedevelopers.com/magazine/515-how-software-is-steering-vehicle-technology) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development)