Overview In this role you lead a hands-on team of software developers and data scientists focused on diagnostic and quality analytics for Ford vehicles. You drive the end-to-end delivery of analytics products, from data ingestion and model development to production dashboards on scalable GCP infrastructure. You collaborate with product, quality, and engineering stakeholders to translate vehicle diagnostic challenges into reliable data-driven solutions. You will mentor the team, champion agile practices, and shape the analytics product roadmap to improve vehicle quality at scale.
Compensation / Benefits- medical, dental, and prescription coverage
- flexible family care and parental leave
- employee vehicle discount program
- tuition assistance
- employee resource groups
- paid time off and holidays
Responsibilities- Lead a multidisciplinary team delivering diagnostics and quality analytics products
- Oversee end-to-end ML pipelines on GCP (data ingestion, processing, modeling, deployment, monitoring)
- Develop Angular dashboards to present diagnostic insights to internal stakeholders
- Partner with quality, engineering, and product teams to translate needs into technical solutions
- Drive model validation, performance monitoring, and continuous improvement for production-grade reliability
- Manage delivery priorities, risks, and dependencies to align with the product roadmap
- Foster a collaborative, high-performing team culture focused on customer value and quality
- Promote agile practices (sprint planning, backlog refinement, retrospectives) and strong software engineering practices (CI/CD, testing, code reviews)
- Support MLOps adoption for model deployment, monitoring, and lifecycle management
- Stay current on advances in automotive diagnostics, AI/ML, and cloud technologies
Key requirements- 5+ years of relevant experience in data science, ML, analytics, or software engineering
- Proven experience leading or supervising software developers or data scientists
- Experience delivering data science/AI/analytics/software products through development, deployment, and improvement
- Experience with agile methodologies (Scrum or Kanban)
- Strong analytical and problem-solving skills; ability to communicate complex topics clearly
- Knowledge of automotive diagnostics including DTCs, DIDs, and CAN bus data
- Proficiency in Python for data manipulation and model development
- Strong understanding of ML methods including deep learning and ensembles
- Experience with ML frameworks (TensorFlow, Keras, PyTorch) and end-to-end ML pipelines
- Experience on GCP (AI Platform, BigQuery, Dataflow, TensorFlow) and cloud-based data storage/processing
- Familiarity with Docker for packaging/deploying software or models
- Experience with Git and solid software engineering practices (testing, code review)
- Strong communication of technical concepts to diverse stakeholders
- Collaborative mindset and ability to lead cross-functional teams
- Mentorship and career development orientation
- Python for data science and ML
- ML/AI methods including deep learning and ensemble models
- TensorFlow, Keras, or PyTorch
