Data Scientist

Ford Motor Company

. Design ML data products using robust coding practices .

Posted 10/23/2026full-timeRemote • MexicoMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and deploying machine learning data products, with strong proficiency in Python and experience in data preparation, model training, and API development. Capable of collaborating effectively across teams while communicating technical findings to diverse audiences.

Highest-signal resume keywords

Machine Learning Model DevelopmentPython ProgrammingAPI Development with FastAPIData Preparation and AnalysisDeployment on Google Cloud Platform

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Machine LearningDeep LearningStatistical AnalysisData CleaningModel TrainingPythonNumPyPandasScikit-learnREST API Development

Soft Skills

CollaborationCommunicationProblem-SolvingAdaptabilityTeamwork

Tools & Technologies

DockerKubernetesGitGitHubGoogle Cloud PlatformStreamlitDashPlotlyFastAPIAgent Development Kit (ADK)

Industry Keywords

Automotive IndustryAI ApplicationsGenerative AINatural-Language ProcessingData PipelinesCloud-Based AnalyticsDistributed ProcessingCI/CDProduction MonitoringVector Search

Tech Stack

Tools & technologies

CloudDockerGoogle Cloud PlatformKubernetesNumpyPandasPythonScikit-Learn

About the role

Key responsibilities & impact

Design ML data products using robust coding practices
Analyze, clean, and prepare structured and unstructured data for modeling and AI applications
Perform statistical analysis and preprocessing on large datasets
Explore state-of-the-art models and techniques for automotive industry use cases
Conduct machine learning experiments to train and infer models, including models subject to memory and latency restrictions
Deploy REST APIs or minimalistic UI applications using Docker and Kubernetes
Showcase machine learning, deep learning, and generative AI applications through Dash, Plotly, Streamlit, and similar web frameworks
Build modular AI/ML products for scalable consumption
Develop agentic applications using Google’s Agent Development Kit (ADK), integrating agents with tools, data, and application workflows
Use Git and GitHub for version control, collaboration, code review, and project workflows
Communicate findings, trade-offs, and recommendations to technical and non-technical partners

Requirements

What you’ll need

3+ years of experience
Bachelor’s or Master’s Degree in Computer Science, Engineering, Maths or Science
Strong Python skills; experience with NumPy, Pandas, and scikit-learn
Ability to write readable, testable, and maintainable code
Experience selecting, training, and evaluating machine learning models
Understanding of data preparation, validation, metrics, and common sources of bias or leakage
Experience developing APIs or services with FastAPI or comparable frameworks
Ability to build interfaces with Streamlit or similar tools
Experience deploying or supporting data and AI workloads on Google Cloud Platform
Familiarity with Google’s Agent Development Kit (ADK), or comparable agent frameworks and willingness to learn ADK
Comfortable with Git and GitHub branching, commits, pull requests, code review, and collaborative development
Helpful experience with deep learning, natural-language processing, generative AI, retrieval-based applications, Docker, automated testing, dependency and environment management, CI/CD, production monitoring, data pipelines, distributed processing, cloud-based analytics, vector search, search platforms, or unstructured data
Comfortable collaborating across teams and locations using GitHub, chat, email, and video calls