AI Savvy Data Analyst (English version)

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          "text": "<p><strong>Data Analyst – AI focused in Hardware Manufacturing, Quality &amp; Reliability</strong></p><p><strong>Role Summary</strong></p><p>This role sits at the intersection of <strong>data analytics, hardware manufacturing, quality &amp; reliability engineering, and digital transformation</strong>. 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.</p><p>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.</p><p><strong>Key Responsibilities</strong></p><p><strong>Data Analysis &amp; Engineering</strong></p><ul><li>Extract, transform, and analyze fleet‑scale manufacturing, testing, deployment, and operational data using advanced SQL (DML).</li><li>Understand and translate manufacturing, quality, and reliability concepts into measurable, data‑driven solutions and KPIs.</li><li>Perform statistical analysis on manufacturing test data to ensure data integrity, reliability, and readiness for automation and root‑cause analysis.</li><li>Continuously provide feedback upstream to improve data quality, coverage, and performance.</li></ul><p><strong>AI, Automation &amp; Intelligence</strong></p><ul><li>Identify and implement opportunities to automate manual workflows using AI and advanced analytics.</li><li>Develop AI‑driven recommendation systems for data standards, anomaly detection, intelligent data mapping, and quality insights.</li><li>Support the integration of AI and ML services (e.g., Vertex AI, LLMs) into analytics workflows and intelligent applications.</li><li>Partner with engineers and product teams to embed AI capabilities into hardware NPI and manufacturing processes.</li></ul><p><strong>Visualization, Reporting &amp; Executive Insights</strong></p><ul><li>Design, develop, and maintain interactive dashboards and reports using Looker Studio, Tableau, Power BI, or equivalent tools.</li><li>Visualize manufacturing performance, data quality scores, operational metrics, headcount status, and organizational spending.</li><li>Prepare executive‑level summaries and presentations that distill complex technical data into clear, actionable insights.</li><li>Provide leadership with real‑time, decision‑ready visibility into manufacturing and operational health.</li></ul><p><strong>Cross</strong>‑<strong>Functional Collaboration &amp; Program Support</strong></p><ul><li>Interact professionally with engineers, product owners, suppliers, and subject‑matter experts across manufacturing, quality, IT, and operations.</li><li>Provide technical guidance to suppliers and engineering teams on optimal data collection, standards, and data warehousing solutions.</li><li>Support multiple parallel initiatives by tracking progress, identifying risks, and escalating delivery impediments when needed.</li><li>Facilitate change management through documentation, communication plans, and process training.</li></ul>",
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          "text": "<p><strong>The ideal candidate in a few words:</strong></p><p><strong>Required Qualifications</strong></p><ul><li>Bachelor’s degree in Computer Science, Data Science, Data Analytics, Statistics, Mathematics, Engineering, or a related discipline.</li><li>Advanced proficiency in SQL with strong understanding of data modeling and normalization best practices.</li><li>Proficiency in Python (or R) for data analysis, including experience with the PyData stack (NumPy, Pandas, Matplotlib, scikit‑learn).</li><li>Strong analytical, problem‑solving, and statistical analysis skills.</li><li>Proven experience creating dashboards, reports, and structured datasets to support business and engineering decisions.</li><li>Excellent verbal and written communication skills in English.</li></ul><p>&#xa0;</p><p><strong>Preferred / Nice</strong>‑<strong>to</strong>‑<strong>Have Qualifications</strong></p><ul><li>5+ years of experience working with cloud data warehouses such as Google BigQuery or equivalent platforms.</li><li>Familiarity with Google Cloud data products (Vertex AI, Colab, Cloud APIs).</li><li>5+ years of experience building interactive dashboards in Looker Studio, Tableau, Power BI, or similar tools.</li><li>Practical experience with AI/ML models, Large Language Models (LLMs), and AI‑enabled workflow automation.</li><li>Domain experience in electronics manufacturing processes, quality engineering, test engineering, or reliability engineering.</li><li>Exposure to data governance, data quality management, or master data management concepts.</li><li>Familiarity with operational topics such as headcount planning, resource allocation, or vendor/contractor (TVC) tracking.</li><li>Fluency in English, Mandarin or French is a plus.</li></ul>",
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          "text": "<p><strong>The Averna experience</strong></p><p>Averna delivers industry-leading test solutions and services for communications and electronics device makers worldwide, accelerating product development, quality and innovation:</p><ul><li><strong>Be global@work</strong>: Serve international customers and collaborate with colleagues in Canada, Europe, the U.S., Mexico and Asia.</li><li><strong>Drive innovation@work</strong>:&#xa0;Participate in the development of market-leading high-tech products in the Automotive &amp; Transportation, Electric Vehicles, Consumer Electronics, Industrials and Life Sciences.&#xa0;&#xa0;</li><li><strong>Develop your talent@work</strong>: Contribute to thrilling projects that will stretch your skills and talent to the maximum.</li><li><strong>Enjoy success@work</strong>: Be part of a fast-growing company with award-winning products and team.</li><li><strong>Share your passion@work</strong>: Meet passionate people, enjoy our modern environment and dynamic atmosphere.</li></ul>",
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