Safety Field Investigations – Data Analyst

• Lead field action VIN population analysis and definition to determine vehicle eligibility, support customer contact strategy, and help complete required documentation.
• Design, maintain, and improve data pipelines and data workflows that support field action analytics, reporting, and operational decision-making.
• Perform data preprocessing, cleansing, validation, and feature engineering to improve data quality and usability for analysis.
• Develop cost estimates and analytical models to support corporate financial accruals and business planning.
• Create and distribute internal field performance and field action communications for global and regional stakeholders.
• Support the administration, enhancement, and data governance of the Global SFI database and related analytical tools.
• Build dashboards, scorecards, and self-service reporting solutions using Tableau and Power BI to monitor field action performance and trends.
• Use SQL, Databricks, Hadoop, Pandas, and Num Py to analyze large datasets, automate recurring analysis, and generate actionable insights.
• Partner with engineering, operations, and global teams to solve complex problems, align on data definitions, and drive consensus on key decisions.
• Apply knowledge of automotive engineering terms, systems, and components to interpret data and support field action execution.

• Bachelor’s degree in Data Analytics, Computer Science, Information Systems, or a related field; equivalent relevant experience may be considered.
• 5+ years of related experience or demonstrated proficiency in analytical and technical roles.
• Strong oral and written communication skills.
• Strong interpersonal skills and the ability to work effectively with cross-functional and global partners.
• Demonstrated ability to work independently, solve highly complex problems, and lead teams to consensus when needed.
• High level of analytical ability, especially when working with unusual or difficult problems.
• Strong experience with SQL and data analysis in large, complex datasets.
• Hands-on experience with data engineering and big data environments such as Databricks and Hadoop.
• Experience building and maintaining data pipelines and performing data preprocessing and feature engineering.
• Experience creating dashboards and visual analytics using Tableau and Power BI.
• Proficiency with Python-based analytics tools such as Pandas and Num Py.
• Strong estimating, planning, and organizational skills.

Demonstrates expertise in data analysis, data engineering, and the development of analytical models to support business planning and decision-making. Proficient in building data pipelines, creating visual analytics, and collaborating with cross-functional teams to drive consensus and solve complex problems.

• Data Pipeline Development
• SQL Proficiency
• Tableau Dashboard Creation
• Data Engineering with Databricks
• Analytical Model Development

• Data Analysis
• Data Preprocessing
• Feature Engineering
• Cost Estimation
• Analytical Modeling
• Data Validation
• Data Cleansing
• Big Data Environments
• Automated Analysis
• Data Governance

• Strong Communication Skills
• Interpersonal Skills
• Problem-Solving Ability
• Team Leadership
• Organizational Skills

• Automotive Engineering
• Field Action Analytics
• Data Workflows
• Operational Decision-Making
• Stakeholder Communication

• Tableau
• Power BI
• SQL
• Databricks
• Hadoop
• Pandas
• Num Py