At Lucid, we set out to introduce the most captivating, luxury electric vehicles that elevate the human experience and transcend the perceived limitations of space, performance, and intelligence
Requirements
- Advanced knowledge of Smartsheet, SQL, JIRA, and Tableau
- Python experience is a plus
- Advanced skills in Microsoft Excel, Word, and PowerPoint
- Experience in the manufacturing Industry (Automotive OEM or Tier 1 Suppliers preferred)
- Experience working in a dynamic/start-up environment is a plus
- Ability to deep-dive data from both a top-down and bottom-up approach
- Ability to think strategically and communicate strategies effectively
Responsibilities
- Analyze complex data sets to identify patterns, trends, and insights for manufacturing and logistics teams
- Present findings and recommendations to senior leadership, translating complex analyses into clear, actionable insights
- Develop and maintain robust dashboards, reports, and visualizations to communicate findings to stakeholders at all levels
- Partner with Data Engineering and Enterprise Systems (MES, SAP, Ignition) teams to set up and streamline data pipelines
- Document business and technical reporting methodology, best practices and related rules for generating reports to ensure results accurately represent the underlying data
- Collaborate with various departments to define key performance indicators (KPIs) and metrics to measure success
- Ensure data integrity and accuracy by implementing best practices in data management and governance
Other
- Bachelor’s degree in engineering, Data Science or equivalent experience in a related field
- 5+ years of experience in data analytics, reporting, visualization, etc
- Excellent communication and interpersonal skills, with the ability to collaborate effectively with cross-functional teams
- Demonstrated project management abilities, including the ability to prioritize tasks, manage timelines, and allocate resources effectively
- Flexibility in work schedule is required (to include evenings and weekends, as needed)
