Ford GDI&A; Industrial Systems Analytics is seeking hands-on data scientists who can develop and deliver practical, reliable data products. You will apply statistical analysis, machine learning, and modern AI—including agentic applications—to automotive and industrial use cases, from exploration and prototyping through deployment and ongoing improvement.
You'll be working as a technical expert in a variety of products involving tabular data predictions, agentic classification/assistance, semantic/search and summarization, platform cloud deployment, and CI/CD pipelines among others.

Experience : 3+ years
Education : Bachelor’s or Master’s Degree in Computer Science, Engineering, Maths or Science

Core Technical Requirements:
Python and Data Science:
• Strong Python skills; experience with NumPy, Pandas, and scikit-learn. Ability to write readable, testable, and maintainable code.
Machine Learning and Statistics:
• Experience selecting, training, and evaluating appropriate models; understanding of data preparation, validation, metrics, and common sources of bias or leakage.
Application Development:
• Experience developing APIs or services with FastAPI or comparable frameworks. Ability to build clear, useful interfaces with Streamlit or similar tools.
Google Cloud:
• Experience deploying or supporting data and AI workloads on GCP. Relevant services include:
• Vertex AI: model development, evaluation, and managed AI capabilities.
• Cloud Run:



deploying containerized APIs and applications.
• Cloud Storage: data and model artifacts.
• BigQuery: analytical data storage and SQL-based analysis.
• Artifact Registry and Cloud Build: container images and build workflows.
• Cloud Logging and Cloud Monitoring: observability.
• Secret Manager and IAM: secrets and access control.
Specific services depend on the solution; candidates are not expected to have used every service.
Agentic AI:
• Familiarity with Google’s Agent Development Kit (ADK), or comparable agent frameworks and a willingness to learn ADK.
Git and GitHub:
• Comfortable with branching, commits, pull requests, code review, and collaborative development.
Helpful Additional Experience:
• Deep learning, natural-language processing, generative AI, or retrieval-based applications.
• Docker and container-based development.
• Automated testing, dependency and environment management, CI/CD, or production monitoring.
• Data pipelines, distributed processing, or cloud-based analytics.
• Vector search, search platforms, or unstructured data.
Collaboration:
We value clear communication, thoughtful technical judgment, teamwork, and the ability to explain complex results to a broad audience. Candidates should be comfortable collaborating across teams and locations using GitHub, chat, email, and video calls.

undefined

📌 Data Scientist (Ciudad de México)
🏢 Ford Motor
📍 Ciudad de México