Data Analyst
RemoteUnited States
Job Summary
Extract, transform, and analyze fleet-scale manufacturing, testing, and deployment data using advanced SQL to ensure data integrity for root-cause analysis. Translate complex quality and reliability concepts into measurable KPIs, intelligent dashboards, and AI-enabled applications while automating manual workflows. Develop AI-driven recommendation systems for anomaly detection and partner with engineering teams to embed machine learning services into hardware NPI processes. Design interactive reports in Looker Studio or Tableau to visualize operational metrics and prepare executive summaries that distill technical data into actionable insights. Collaborate cross-functionally with suppliers and subject-matter experts to establish data standards and track program progress.
Required Qualifications
- Bachelor's degree in Computer Science, Data Science, Data Analytics, Statistics, Mathematics, Engineering, or a related discipline.
- Advanced proficiency in SQL with strong understanding of data modeling and normalization best practices.
- Proficiency in Python (or R) for data analysis, including experience with the PyData stack (NumPy, Pandas, Matplotlib, scikit-learn).
- Strong analytical, problem-solving, and statistical analysis skills.
- Proven experience creating dashboards, reports, and structured datasets to support business and engineering decisions.
- Excellent verbal and written communication skills in English.
Desired Qualifications
- 5+ years of experience working with cloud data warehouses such as Google BigQuery or equivalent platforms.
- Familiarity with Google Cloud data products (Vertex AI, Colab, Cloud APIs).
- 5+ years of experience building interactive dashboards in Looker Studio, Tableau, Power BI, or similar tools.
- Practical experience with AI/ML models, Large Language Models (LLMs), and AI-enabled workflow automation.
- Domain experience in electronics manufacturing processes, quality engineering, test engineering, or reliability engineering.
- Exposure to data governance, data quality management, or master data management concepts.
- Familiarity with operational topics such as headcount planning, resource allocation, or vendor/contractor (TVC) tracking.
- Fluency in Mandarin or French is a plus.
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