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AI & Analytics Implementation Specialist

Ford Motor Company

  • Dearborn, MI
  • 10 days ago

    Highlights

    Design and Develop Analytics solutions and integrate Models using Vendor tools, GCP services such as BigQuery, PostgreSQL, Cloud Functions, Cloud Storage, Cloud Composer, Cloud Run, and Pub/Sub to build scalable workflows that support analytics delivery. You will be a key contributor in building scalable, automated analytics workflows and applying Agentic AI frameworks to streamline reporting, data summarization, and validation processes.

    Numbers & Facts

    LocationDearborn, MI

    Description

    We made history and now we work to transform the future - for our customers, our communities and our families. You'll see your work on the road every day, helping people move freely and pursue their dreams. At Ford, you can build more than vehicles. Come build what matters.

    Do you believe data tells the real story? We do! Redefining mobility requires quality data, metrics and analytics, as well as insightful interpreters and analysts. That's where Global Data Insight & Analytics makes an impact. We advise leadership on business conditions, customer needs and the competitive landscape. With our support, key decision makers can act in meaningful, positive ways. Join us and use your data expertise and analytical skills to drive evidence-based, timely decision making.

    In this position...

    In this role, you will bridge the gap between analytical model development and production deployment, using SAS, vendor tools, on-prem systems, and cloud-based applications. You will be a key contributor in building scalable, automated analytics workflows and applying Agentic AI frameworks to streamline reporting, data summarization, and validation processes. This is a dynamic opportunity for someone who enjoys innovation, problem-solving, and leveraging advanced technologies to accelerate real-world business processes.

    AI & Analytics Implementation Specialist

    What you'll do...

    • Implement, validate, test, and productionalize predictive models and risk strategies across global platforms.

    • Design and Develop Analytics solutions and integrate Models using Vendor tools, GCP services such as BigQuery, PostgreSQL, Cloud Functions, Cloud Storage, Cloud Composer, Cloud Run, and Pub/Sub to build scalable workflows that support analytics delivery.

    • Collaborate with Data Scientists, Business teams, and IT to ensure smooth transition of models from development to production.

    • Identify opportunities to introduce automation, GenAI tooling, and workflow simplification; develop proof-of-concepts and enhance delivery processes through automation.

    • Provide data analysis, SQL/SAS/Python programming, and on-demand reporting aligned to business needs.

    • Develop reusable and repeatable automation frameworks for data comparison, summarization, and reporting across multiple business functions and systems.

    • Design and implement automated pipelines that support testing workflows, with occasional integration involving legacy or mainframe-adjacent data sources.

    What you'll do...

    • Implement, validate, test, and productionalize predictive models and risk strategies across global platforms.

    • Design and Develop Analytics solutions and integrate Models using Vendor tools, GCP services such as BigQuery, PostgreSQL, Cloud Functions, Cloud Storage, Cloud Composer, Cloud Run, and Pub/Sub to build scalable workflows that support analytics delivery.

    • Collaborate with Data Scientists, Business teams, and IT to ensure smooth transition of models from development to production.

    • Identify opportunities to introduce automation, GenAI tooling, and workflow simplification; develop proof-of-concepts and enhance delivery processes through automation.

    • Provide data analysis, SQL/SAS/Python programming, and on-demand reporting aligned to business needs.

    • Develop reusable and repeatable automation frameworks for data comparison, summarization, and reporting across multiple business functions and systems.

    • Design and implement automated pipelines that support testing workflows, with occasional integration involving legacy or mainframe-adjacent data sources.

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