Analytics Engineer

• Analyze warranty, connected-vehicle, diagnostic, and other quality data to identify emerging defect trends, potential quality escapes, and leading indicators
• Partner with Product Development, Design and Release Engineering, Powerpack Quality Engineering, and other IPTSE teams on root-cause investigations and corrective actions
• Develop processes, tools, and methods to collect, manipulate, unify, and analyze large connected-vehicle data sets
• Promote and apply Agile Data Collection methods and tools, including RDR, PARSED, CARMon, ADC Lua scripting, Data Canvas, Alteryx, and macros
• Automate end-to-end data flows for collection, anomaly detection, transformation, manipulation, and quality-metric delivery
• Build dashboards, automated trend reports, executive-level presentations, and clear data visualizations
• Classify warranty claims by failure mode
• Summarize customer verbatims
• Identify emerging defect trends and potential quality escapes
• Support AI-assisted root-cause investigation summaries
• Apply natural-language-processing techniques to predictive modeling
• Develop and document data, AI, and analytics practices
• Support Six Sigma, 8D, DMAIC, CPR, and other corrective-action processes
• Modernize Quality Methods documentation and coach Powerpack Quality Engineers
• Serve as a key point of contact for Cloud-Assisted Diagnostics and ATIS/HTIS end-to-end integration activities
• Transfer identified data issues, opportunities, and system improvements to appropriate teams
• Build relationships with business partners across Ford North American organizations

Quality Analytics Engineer

• Write SQL that transforms raw data into structured datasets as part of a data pipeline and makes them usable in dashboards
• Support existing reporting and develop new reporting and dashboard work
• Design and build SQL data models connecting to a source dataset
• Build a Looker Studio dashboard
• Validate the dashboard with a stakeholder and present the dashboard and findings
• Conduct data quality checks and identify and troubleshoot common data issues
• Collaborate with stakeholders to ensure dashboard deliverables answer the business question being asked
• Present findings and recommendations to technical and non-technical audiences
• Use AI coding assistants to accelerate work while understanding, verifying, and explaining all code

Analytics Engineer Intern

• Partner with business teams to understand their goals and data needs
• Build and validate data models using SQL, Python, and Databricks
• Use AI coding assistants in day-to-day workflow
• Analyze data, identify quality issues, and develop practical solutions
• Test, document, and improve work based on feedback
• Present final project and recommendations to business and Decision Intelligence leaders
• Complete a 10-week summer internship with real projects and responsibility
• Participate in executive speaker series, business segment overviews, mentor relationships, site visits, community outreach, and networking opportunities
• Present a Final Capstone Project

Analytics Engineer jobs in Michigan

Quality Analytics Engineer

Analytics Engineer Intern

Analytics Engineering Intern