Overview:
Mopar is seeking a technically skilled and innovative Data Engineer / Data Scientist to drive advanced analytics and data solutions. This role is central to designing, building, and optimizing data pipelines, developing predictive models, and delivering actionable insights that empower HQ stakeholders. The ideal candidate will blend strong engineering skills with analytical expertise to support data-driven decision-making and operational excellence across the region.
Key Responsibilities:
Data Engineering & Pipeline Development:
- Design, implement, and maintain robust data pipelines (ETL/ELT) to collect, process, and transform large-scale structured and unstructured datasets from diverse automotive sources.
- Ensure data quality, integrity, and accessibility by developing automated validation and monitoring tools.
- Optimize data workflows for performance, scalability, and reliability, supporting both batch and real-time analytics needs.
- Collaborate with IT and analytics teams to integrate data from business systems into centralized data products.
Advanced Analytics & Data Science:
- Analyze complex datasets to uncover trends, patterns, and actionable insights that inform business strategies and operational improvements.
- Build, train, and deploy predictive models and machine learning algorithms for applications such as performance forecasting, anomaly detection, and customer segmentation.
- Conduct A/B testing, causal inference, and statistical analysis to evaluate business initiatives and drive continuous improvement.
- Apply best practices in data visualization to ensure clarity, accuracy, and accessibility of insights, including interactive dashboards, automated reporting, and mobile-friendly solutions.
Collaboration & Stakeholder Engagement:
- Serve as a technical liaison between HQ analytics and business teams, translating business needs into scalable data solutions.
- Educate and mentor team members on data best practices, analytics tools, and emerging technologies.
