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hace 2 días

Naucalpan, México Ford Motor Company A tiempo completo

Ford Motor Company's GDIA organization is seeking a skilled data scientist to analyze Ford's quality data and customer feedback to identify areas for improvement. In this role, you will work closely with cross-functional teams including quality engineering, manufacturing, and customer care to guide data-driven decisions around vehicle quality and customer satisfaction.**Key Responsibilities**:- Analyze Ford's warranty claims data to identify defect trends in vehicle components/systems, common quality issues, and opportunities to reduce future warranty costs.- Mine voice of the customer data sources (surveys, social media, etc.) to surface top customer pain points around quality and product reliability.- Continuously improve the efficiency and accuracy of existing machine learning models.- Develop scalable model architectures for fast and reliable model retraining purposes.- Document and communicate findings and insights to stakeholders in a clear and concise manner.**Minimum Requirements**:- Master’s degree in computer science, Statistics, Mathematics, Engineering, or a related quantitative field.- Minimum of two years of experience in Python programming language.- 1+ years’ experience in SQL programming language and relational databases.- 2+ years of experience with data analysis and visualization Python packages such as Pandas, SciPy, Seaborn, etc.- 2+ years of experience with supervised machine learning algorithms and at least one of the following popular Machine learning frameworks: Scikit-learn, Pytorch, TensorFlow, and XGBoost.**Preferred Qualifications**:- Ph.D. degree in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field is preferred.- Experience with Git and GitHub for version control and collaboration.- Experience with Google Cloud Platform for data processing and machine learning tasks.- Solid understanding of unsupervised machine learning algorithms such as isolation forests, one-class SVM, autoencoders, etc.- Familiarity with feature engineering concepts, Fourier transform, and statistical feature extraction and selection.- Excellent problem solving, communication, and data presentation skills.

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