Analytics Integration Specialist

Ford Motor CompanyDearborn, MI
$99,600 - $166,600Onsite

About The Position

Ford Motor Credit Company’s Global Data Insights & Analytics (GDIA) organization is seeking a highly motivated and technically skilled professional to join the Analytics Solutions Integration team within Credit Analytics. This position is ideal for professionals excited about implementing and productionalizing the predictive models for multiple business functions, modernizing legacy processes, and applying advanced technologies to transform analytics delivery. In this role, you will bridge the gap between analytical model development and production deployment, using SAS, Vendor tools on OnPrem and Cloud-based applications. You will also be a key contributor in modernizing legacy mainframe-based batch testing processes through automation, dataset comparison frameworks, and summarization/reporting of the data and application of Agentic frameworks. This is a dynamic opportunity for someone who enjoys innovation, problem‑solving, and leveraging advanced technologies to streamline and accelerate real-world business processes.

Requirements

  • Technical skills
  • Experience with SAS
  • Experience with Vendor tools on OnPrem and Cloud-based applications
  • Experience with automation
  • Experience with dataset comparison frameworks
  • Experience with summarization/reporting of data
  • Experience with Agentic frameworks

Nice To Haves

  • Highly motivated
  • Excited about implementing and productionalizing predictive models
  • Excited about modernizing legacy processes
  • Excited about applying advanced technologies to transform analytics delivery
  • Enjoys innovation
  • Enjoys problem-solving
  • Enjoys leveraging advanced technologies to streamline and accelerate real-world business processes

Responsibilities

  • Implementing and productionalizing predictive models for multiple business functions.
  • Modernizing legacy processes.
  • Applying advanced technologies to transform analytics delivery.
  • Bridging the gap between analytical model development and production deployment using SAS, Vendor tools on OnPrem and Cloud-based applications.
  • Modernizing legacy mainframe-based batch testing processes through automation, dataset comparison frameworks, and summarization/reporting of the data and application of Agentic frameworks.
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