Description

Job Summary Job Summary Ford’s Global Data Insights & Analytics (GDI&A) team is seeking an experienced Data Scientist to develop scalable, data-driven solutions for complex real-world business problems. This role focuses on leveraging Machine Learning, Big Data, Statistics, and Advanced Analytics to deliver actionable insights across domains such as Connected Vehicles, Smart Mobility, Manufacturing, Supply Chain, Logistics, and Quality Analytics, enabling evidence-based decision-making at scale. Key Responsibilities Data Analysis & Machine Learning Analyze large, complex datasets to uncover patterns, trends, and actionable insights Design, develop, and deploy machine learning models using supervised and unsupervised techniques Apply advanced analytics methods including predictive, prescriptive, and statistical modeling Design and execute experiments, hypotheses, and validation strategies to support data-driven decisions Business Intelligence & Visualization Develop and maintain interactive dashboards and reports using Power BI Translate complex analytical results into clear, intuitive visualizations for business stakeholders Build dynamic user interfaces and reports using data stored on Google Cloud Platform (GCP) Data Engineering & Model Scalability Design efficient data loading, data augmentation, and data preprocessing pipelines Build scalable and automated analytics and ML solutions suitable for enterprise deployment Ensure model accuracy, robustness, and performance through continuous optimization Collaboration & Stakeholder Engagement Partner with business teams to understand requirements and recommend analytical approaches Communicate insights and recommendations to technical and non-technical audiences Support decision-making across supply chain, manufacturing, logistics, and operations teams Innovation & Continuous Learning Stay current with emerging trends in data science, machine learning, and analytics tools Proactively identify opportunities to improve analytical efficiency, accuracy, and impact Required Qualifications Bachelor’s degree in Computer Science, Statistics, Applied Mathematics, Operational Research, Engineering, or a related field 2+ years of experience in Python-based data analysis and machine learning Strong hands-on experience with NumPy, Pandas, Matplotlib, Seaborn, Scikit-learn Experience with TensorFlow or PyTorch and NLP libraries such as NLTK, spaCy, or Gensim 2+ years of experience applying supervised and unsupervised ML techniques 2+ years of experience building dashboards and reports using Power BI 1+ year of experience with SQL and relational databases Preferred Skills Experience with Big Data and Cloud platforms, particularly Google Cloud Platform (GCP) Exposure to Dash, QlikSense, or similar visualization tools Domain knowledge in Manufacturing, Supply Chain, Logistics, or Quality Analytics Strong understanding of automation and scalable analytics solutions Tools & Technologies Python, SQL, Power BI, NumPy, Pandas, Matplotlib, Seaborn, Scikit-learn, TensorFlow, PyTorch, NLP libraries (NLTK, spaCy, Gensim), GCP, Dash, QlikSense Key Skills Data Science, Machine Learning, Data Analysis, Business Intelligence, Data Mining, Python, SQL, Supply Chain Analytics, Logistics Analytics, Automation About Ford Motor Company Ford is a global automotive leader driven by a strong sense of purpose—to help build a better world where everyone is free to move and pursue their dreams. With a legacy of innovation and a commitment to smart mobility, sustainability, and advanced technology, Ford’s global workforce collaborates to shape the future of transportation and deliver meaningful impact for people, communities, and the planet.

Role and Responsibilities

• Job Summary Ford’s Global Data Insights & Analytics (GDI&A) team is seeking an experienced Data Scientist to develop scalable, data-driven solutions for complex real-world business problems. This role focuses on leveraging Machine Learning, Big Data, Statistics, and Advanced Analytics to deliver actionable insights across domains such as Connected Vehicles, Smart Mobility, Manufacturing, Supply Chain, Logistics, and Quality Analytics, enabling evidence-based decision-making at scale. Key Responsibilities Data Analysis & Machine Learning Analyze large, complex datasets to uncover patterns, trends, and actionable insights Design, develop, and deploy machine learning models using supervised and unsupervised techniques Apply advanced analytics methods including predictive, prescriptive, and statistical modeling Design and execute experiments, hypotheses, and validation strategies to support data-driven decisions Business Intelligence & Visualization Develop and maintain interactive dashboards and reports using Power BI Translate complex analytical results into clear, intuitive visualizations for business stakeholders Build dynamic user interfaces and reports using data stored on Google Cloud Platform (GCP) Data Engineering & Model Scalability Design efficient data loading, data augmentation, and data preprocessing pipelines Build scalable and automated analytics and ML solutions suitable for enterprise deployment Ensure model accuracy, robustness, and performance through continuous optimization Collaboration & Stakeholder Engagement Partner with business teams to understand requirements and recommend analytical approaches Communicate insights and recommendations to technical and non-technical audiences Support decision-making across supply chain, manufacturing, logistics, and operations teams Innovation & Continuous Learning Stay current with emerging trends in data science, machine learning, and analytics tools Proactively identify opportunities to improve analytical efficiency, accuracy, and impact