Top Automotive Data & Analytics Jobs

The Senior Ad Ops Engineer develops and manages data products for marketing activation, focusing on data pipelines, quality validation, and integration with marketing platforms.

The Lead, Sales Analytics & Business Intelligence will analyze data, drive business strategy, and provide insights to enhance sales growth and profitability.

Lead a global analytics team to transform financial and operational data into actionable insights. Partner with stakeholders to align analytics with strategy, build scalable Power BI dashboards integrated with Snowflake, apply predictive modeling and ML, enforce data governance, drive automation with Python and Power Automate, and improve data architecture and reporting to inform decision-making and business performance.

The Lead Data Analyst (Network) drives data-driven initiatives, dissects datasets, and provides actionable insights to enhance business performance and network efficiency.

The Business Intelligence Sr Analyst executes data-driven analysis and builds AI-powered workflows to provide insights to Cox Automotive's leadership and clients, leveraging advanced data analytics and statistical methods.

The Manager of Media Analytics & Optimization will lead media performance measurement, drive insights for decision-making, and foster collaboration with senior stakeholders, while utilizing skills in analytics and AI.

As a Data Engineer at Edmunds, you will architect and maintain data platforms for analytics and AI/ML, ensuring scalable, reliable data processing and supporting cross-functional collaboration.

The Inventory Analyst is responsible for managing inventory and supply chain processes within the automotive sector, ensuring efficiency and compliance with company standards. The role requires assessing performance and adhering to training protocols.

The Data Analyst in Revenue Operations will analyze sales data, build models, and create reports using SQL, Excel, and BI tools to empower business decisions.

The role involves building scalable data platforms, developing data pipelines, mentoring engineers, and enhancing data security while collaborating across teams.