Automotive Warranty Claim Data Lead

Key Responsibilities

• Data Strategy & Analytics Leadership
• Lead the development, implementation, and maintenance of advanced analytical models (e.g., predictive models, time-series forecasting) to project future warranty claims, failure rates, and cost trends.
• Spearhead deep-dive analysis on complex warranty datasets to uncover root causes of product failures, identify anomalies, and detect potential over repairs.
• Develop and manage the overall data governance strategy for the warranty claims database, Palantir/MAP, to ensure data accuracy, consistency, and reliability across all reporting and analytical platforms.
• Design, build, and maintain intuitive data dashboards and Key Performance Indicators (KPIs) to monitor group warranty goals, claim trends/broken clean points, and product reliability for all relevant stakeholders.
• Reporting & Cross-Functional Collaboration
• Prepare and present regular, comprehensive reports on warranty performance, cost drivers, and key findings to senior management, including executive-level summaries.
• Collaborate cross-functionally with Quality, Engineering, Manufacturing, and Service teams to translate data insights into concrete product or process improvements.
• Provide actionable intelligence to the Technical Service team, enabling faster resolution of recurring and high-cost failure modes in the field.
• Support the Finance and Accounting departments with accurate warranty cost accruals, budget forecasting, and financial reporting based on data-driven projections.
• Process & System Improvement
• Identify opportunities to leverage advanced technologies, such as Machine Learning or AI, to enhance data mining, claims validation, and root cause analysis processes.
• Act as the subject matter expert and system administrator for key warranty and data platforms (e.g., Global Warranty Management System, BI tools, data warehouses).
• Champion continuous process improvement within the warranty data workflow, seeking to automate data pipelines and streamline reporting to improve efficiency.
• Ensure all data handling and reporting complies with company policies, legal requirements, and industry standards.

Required Qualifications

• Bachelor’s degree in Data Science, Statistics, Engineering, Computer Science, or a related quantitative technical field.
• 5+ years of experience in data analysis, business intelligence, or data science.
• 3+ years of experience specifically within the automotive, manufacturing, or heavy-equipment industry, with a focus on warranty data, reliability engineering, or technical services.
• Proven experience in a leadership or lead-analyst role, mentoring junior team members or managing complex analytical projects.

Preferred Qualifications

• Master’s degree.
• Proficiency in SQL for complex data querying, manipulation, and analysis of large datasets.
• Programming skills in a statistical or data science language, such as Python or R.
• Proficiency with Business Intelligence and data visualization tools (e.g., Tableau, Power BI, QlikSense) to create insightful reports and dashboards.
• Familiarity with warranty management systems (e.g., Global Warranty Management) and enterprise data environments (e.g., data lakes, cloud platforms like AWS, Azure, or GCP).
• Solid understanding of statistical methodologies for time-to-failure analysis (e.g., Weibull), forecasting, and hypothesis testing.
• Knowledge of quality improvement methodologies (e.g., Six Sigma, FMEA).
• Experience with machine learning frameworks and modeling for predictive maintenance or failure prediction.
• Prior experience working directly with automotive dealer management systems (DMS) data.
• Analytical and Problem-Solving Skills: Exceptional ability to interpret complex technical and financial data, distill key findings, and propose practical solutions.
• Communication: Excellent verbal and written communication skills, with the ability to clearly articulate complex technical analysis to both technical and non-technical audiences, including executive leadership.
• Leadership and Influence: Demonstrated ability to lead projects, drive change across cross-functional teams, and influence key stakeholders without direct reporting authority.
• Attention to Detail: Rigorous attention to detail to ensure the accuracy and integrity of all data and analytical reports.