We are trusted advisers enabling Ford to see our business, know our customers and act in a meaningful way. We drive evidence-based decision making by providing timely, actionable and forward-looking insights to our One Ford business partners.
Responsible for integrating market and consumer analytic work streams.
Leading new initiatives in the area of autonomous vehicles and sustainability.
Responsible for supporting connectivity and mobility solutions.
Responsible for developing and implementing risk analytic methodologies across the enterprise.
Responsible for building and operating the global data storage, tooling and computational infrastructure to support Data Operations and Analytics teams.
Responsible for developing and operationalizing data standards, quality, governance and acquiring third party data sources to enable enterprise analytics.
Provide analytic support to corporate staff activities.
Implement the governance framework to identify, prioritize and execute analytic initiatives and drive standardized methodologies and processes globally.
Manage business operations, including governance, business planning and change management.
Responsible for developing new data sources and analytic methods.
In addition to machine learning practitioners in the various departments within GDI&A, there also is a dedicated group of experts in the Machine Learning and Scalable Computing Center of Excellence (ML/SC CoE), whose motto is “Learn, Apply, Master and Teach”. Aligned with that motto, one of the mandates of the CoE is to promote the proliferation of best practices related to ML/SC not only within GDI&A, but also the broader Ford Motor Company enterprise. The CoE fulfills this mandate by serving as internal consultants, as well as offering in-house training opportunities on a variety of topics such as neural nets, deep learning, Spark, and more. Each of these training activities is taught by CoE experts and is customized for the big data computing environment available to all GDI&A employees. In addition, the CoE members maintain their skills by leading their own ML/SC projects for internal Ford customers in a wide variety of domains including marketing, manufacturing, finance and more.
GDI&A data scientists have access to a modern Hadoop computing infrastructure with Spark, consisting of hundreds of nodes with petabytes of usable capacity. In addition to the usual Hadoop software stack, employees have access to a wide variety of additional tools, including, but not limited to Alteryx, Anaconda Python, GitHub Enterprise, Matlab, QlikView, R, and Tableau. For deep learning and other appropriate compute-intensive applications, GDI&A data scientists also have access to powerful workstations, including high-performance CPUs and GPUs. GDI&A has a dedicated department that monitors the organization’s computing needs, and upgrades the infrastructure as needed to meet those needs.
