E2E Warranty Analyst

Ford Motor Company

Dearborn, MI2h agovia LinkedIn

This job at a glance

Who can apply
New grads, no experience needed · Bachelor's degree or Master's degree
Must know
Data analysis
Work
On-site in Dearborn
Pay
Not stated by the employer.
Skill demand
Data analysis25%of 99 similar entry-level jobs posted in the US this week
Listed
Nov 6, 2026 · still open

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About the Role

The E2E Warranty Analyst leads management of prioritized cases (warranty, IQS, etc.) per the Single Agenda for Quality (SAQ) in partnership with Vehicle Function Groups (VFGs) and Functional Quality Managers. This role drives delivery of the throughput standard established for the performance cycle, collaborating with functions to achieve prioritization targets for Time to Detect, Time to Contain, and Time to Resolve. Problem-solving signals originate from various sources including warranty, 14D investigations, and JD Power IQS. Regardless of the signal source, issues are assigned an SAQ priority and processed accordingly, ensuring a consistent approach and appropriate urgency in problem-solving.

Key Responsibilities

  • Lead Problem Solving Throughput and Aging Delivery:
  • Own delivery of overall throughput status and 'phase of problem solving' aging for Functional Units (VHE, EE&S, VE, Paint), collaborating with VFGs, Central Triage Team (CTT), and functional problem solvers.
  • Synthesize signals from IRIS and drive delivery through SIMPSN.
  • Ensure focus on prioritized work per rubric for the performance measurement window.
  • Monitor cases breaching or imminently breaching aging targets, facilitating enablers to mitigate and/or escalate within the function.
  • Enforce process standards for SAQ issues, including active problem-solving teams, robust problem statements, and progression of problem-solving steps.
  • Ensure SAQ is properly scoped and priorities sufficiently address business needs, measured by the percentage of prioritized claims covered by SIMPSN tickets.
  • Ensure forward model-responsible cases are efficiently cascaded through the Long Lead PCA and Prevent Recurrence Action (PRA) processes.
  • Support Program Delivery & Risk Management:
  • Ensure current model quality learnings and functional quality status are accurately reflected in Program Quality Status inputs.
  • Partner with Program Quality (PQ) Engineers to integrate functional quality insights into program-level quality planning.
  • Align current model vehicle line priorities with holistic priorities for functional teams.
  • Cross-Functional Collaboration:
  • Act as a key interface between PQ, engineering, manufacturing, service, and supplier quality teams.
  • Consult with manufacturing and service quality teams to gather insights and integrate their perspectives into functional quality assessments.
  • Drive Current Model Quality Learnings into Future Programs:
  • Engage with engineering teams on current production quality problems to understand root causes and constraints, driving SAQ delivery.
  • Translate complex technical problem resolutions into actionable lessons learned for future vehicle designs and processes.
  • Participate in 'functional waterfall work' to analyze current quality gaps.
  • Enhance Proactive Quality Planning & Data Analysis:
  • Provide real-world insights to the Forward Model Quality (FMQ) team to strengthen Failure Mode Avoidance (FMA) plans, Root Cause (RC) plans, and CTQ (Critical-to-Quality) assessments.
  • Contribute feedback on the effectiveness of Quality Framework Enablers in current production.
  • Lead the identification and cascading of high-performing parts and systems from current models for reuse in future programs.
  • Utilize diverse data sources, including warranty data, customer satisfaction metrics, field service reports, and physical assessment data (e.g., auction data) to identify quality trends and risk areas.

Requirements & Tech Stack

  • Working knowledge of Ford's quality tools and process (or equivalent)
  • Working knowledge of Problem-Solving Methodology (e.g., Global 8D, PDCA)
  • Working knowledge of interpreting quality data sources and applying data analytics
  • IRIS
  • SIMPSN
  • Long Lead PCA
  • Prevent Recurrence Action (PRA)
  • Failure Mode Avoidance (FMA)
  • Root Cause (RC)
  • CTQ (Critical-to-Quality)
  • Warranty data

Qualifications

  • Bachelors Degree in Engineering, Sciences, or academic equivalent, in a closely related technical discipline or equivalent combination of relevant education and experience.
  • Green Belt certification required.

Preferred Qualifications

  • Master's Degree preferred
  • Black Belt certified preferred

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