Analytics Integration Specialist

Ford Ford · Auto · Dearborn, MI +1 · Global Data Insight & Analytics

This role focuses on implementing, validating, testing, and productionalizing predictive models and risk strategies, bridging the gap between analytical model development and production deployment. It involves modernizing legacy processes, automating batch testing workflows, and leveraging cloud services (GCP) and GenAI tooling, including agentic frameworks, to transform analytics delivery.

What you'd actually do

  1. Implement, validate, test, and Productionalize predictive models and risk strategies across global platforms.
  2. Collaborate with Data Scientists, Business teams, and IT to ensure smooth transition of models from development to production.
  3. Design and implement automated pipelines that support batch testing workflows involving mainframe JCL, flat files, VSAM or legacy datasets.
  4. Develop reusable and repeatable automation for compare and summarize data between legacy and modernized systems for multiple business functions.
  5. Use 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.

Skills

Required

  • SAS
  • Java
  • SQL
  • Python
  • GCP
  • RDBMS
  • Agile/Waterfall/PDO methodologies
  • IT testing environments

Nice to have

  • SAS RTDM
  • Master's degree
  • integrating or automating processes involving legacy mainframe systems

What the JD emphasized

  • productionalize predictive models
  • modernizing legacy processes
  • Agentic frameworks
  • GenAI tooling

Other signals

  • productionalizing predictive models
  • modernizing legacy processes
  • applying advanced technologies
  • Agentic frameworks
  • GenAI tooling