AI Savvy Data Analyst
Job Description
Data Analyst - AI focused in Hardware Manufacturing, Quality & Reliability
Role Summary
This role sits at the intersection of data analytics, hardware manufacturing, quality & reliability engineering, and digital transformation. As an AI-savvy Data Analyst, you will generate value-driven insights from fleet-scale manufacturing, test, and deployment data while supporting New Product Introduction (NPI) and Product Operations teams.
You will transform complex manufacturing and quality concepts into data-driven metrics, intelligent dashboards, and AI-enabled applications. You will also lead initiatives that modernize manual workflows into scalable, automated, and insight-driven systems-leveraging statistical analysis, cloud data platforms, and AI technologies.
Key Responsibilities
Data Analysis & Engineering
• Extract, transform, and analyze fleet-scale manufacturing, testing, deployment, and operational data using advanced SQL (DML).
• Understand and translate manufacturing, quality, and reliability concepts into measurable, data-driven solutions and KPIs.
• Perform statistical analysis on manufacturing test data to ensure data integrity, reliability, and readiness for automation and root-cause analysis.
• Continuously provide feedback upstream to improve data quality, coverage, and performance.
AI, Automation & Intelligence
• Identify and implement opportunities to automate manual workflows using AI and advanced analytics.
• Develop AI-driven recommendation systems for data standards, anomaly detection, intelligent data mapping, and quality insights.
• Support the integration of AI and ML services (e.g., Vertex AI, LLMs) into analytics workflows and intelligent applications.
• Partner with engineers and product teams to embed AI capabilities into hardware NPI and manufacturing processes.
Visualization, Reporting & Executive Insights
• Design, develop, and maintain interactive dashboards and reports using Looker Studio, Tableau, Power BI, or equivalent tools.
• Visualize manufacturing performance, data quality scores, operational metrics, headcount status, and organizational spending.
• Prepare executive-level summaries and presentations that distill complex technical data into clear, actionable insights.
• Provide leadership with real-time, decision-ready visibility into manufacturing and operational health.
Cross-Functional Collaboration & Program Support
• Interact professionally with engineers, product owners, suppliers, and subject-matter experts across manufacturing, quality, IT, and operations.
• Provide technical guidance to suppliers and engineering teams on optimal data collection, standards, and data warehousing solutions.
• Support multiple parallel initiatives by tracking progress, identifying risks, and escalating delivery impediments when needed.
• Facilitate change management through documentation, communication plans, and process training.
Qualifications
The ideal candidate in a few words:
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.
Preferred / Nice-to-Have 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.
Additional Information
What's in It for You
• Learn and grow through multiple cutting-edge projects
• Flexible work hours and remote work model #LI-REMOTE
• Competitive benefits package and competitive total compensation
• An additional day off for your birthday
• Flex days paid between Christmas and New year's
• Be part of a company that puts ESG at the heart of its mission, for people, planet, and performance.
Videos To Watch
https://www.youtube.com/watch?v=2B1sxHF205A
Data Analyst - AI focused in Hardware Manufacturing, Quality & Reliability
Role Summary
This role sits at the intersection of data analytics, hardware manufacturing, quality & reliability engineering, and digital transformation. As an AI-savvy Data Analyst, you will generate value-driven insights from fleet-scale manufacturing, test, and deployment data while supporting New Product Introduction (NPI) and Product Operations teams.
You will transform complex manufacturing and quality concepts into data-driven metrics, intelligent dashboards, and AI-enabled applications. You will also lead initiatives that modernize manual workflows into scalable, automated, and insight-driven systems-leveraging statistical analysis, cloud data platforms, and AI technologies.
Key Responsibilities
Data Analysis & Engineering
• Extract, transform, and analyze fleet-scale manufacturing, testing, deployment, and operational data using advanced SQL (DML).
• Understand and translate manufacturing, quality, and reliability concepts into measurable, data-driven solutions and KPIs.
• Perform statistical analysis on manufacturing test data to ensure data integrity, reliability, and readiness for automation and root-cause analysis.
• Continuously provide feedback upstream to improve data quality, coverage, and performance.
AI, Automation & Intelligence
• Identify and implement opportunities to automate manual workflows using AI and advanced analytics.
• Develop AI-driven recommendation systems for data standards, anomaly detection, intelligent data mapping, and quality insights.
• Support the integration of AI and ML services (e.g., Vertex AI, LLMs) into analytics workflows and intelligent applications.
• Partner with engineers and product teams to embed AI capabilities into hardware NPI and manufacturing processes.
Visualization, Reporting & Executive Insights
• Design, develop, and maintain interactive dashboards and reports using Looker Studio, Tableau, Power BI, or equivalent tools.
• Visualize manufacturing performance, data quality scores, operational metrics, headcount status, and organizational spending.
• Prepare executive-level summaries and presentations that distill complex technical data into clear, actionable insights.
• Provide leadership with real-time, decision-ready visibility into manufacturing and operational health.
Cross-Functional Collaboration & Program Support
• Interact professionally with engineers, product owners, suppliers, and subject-matter experts across manufacturing, quality, IT, and operations.
• Provide technical guidance to suppliers and engineering teams on optimal data collection, standards, and data warehousing solutions.
• Support multiple parallel initiatives by tracking progress, identifying risks, and escalating delivery impediments when needed.
• Facilitate change management through documentation, communication plans, and process training.
Qualifications
The ideal candidate in a few words:
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.
Preferred / Nice-to-Have 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.
Additional Information
What's in It for You
• Learn and grow through multiple cutting-edge projects
• Flexible work hours and remote work model #LI-REMOTE
• Competitive benefits package and competitive total compensation
• An additional day off for your birthday
• Flex days paid between Christmas and New year's
• Be part of a company that puts ESG at the heart of its mission, for people, planet, and performance.
Videos To Watch
https://www.youtube.com/watch?v=2B1sxHF205A