AI-savvy Data Analyst generating value-driven insights from manufacturing and operational data in hardware manufacturing. Support NPI and automate workflows with statistical analysis, dashboards and AI.
Responsibilities
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.
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.
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.
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.
Requirements
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.
5+ years of experience working with cloud data warehouses such as Google BigQuery or equivalent platforms (Preferred).
Familiarity with Google Cloud data products (Vertex AI, Colab, Cloud APIs) (Preferred).
5+ years of experience building interactive dashboards in Looker Studio, Tableau, Power BI, or similar tools (Preferred).
Practical experience with AI/ML models, Large Language Models (LLMs), and AI‑enabled workflow automation (Preferred).
Domain experience in electronics manufacturing processes, quality engineering, test engineering, or reliability engineering (Preferred).
Exposure to data governance, data quality management, or master data management concepts (Preferred).
Familiarity with operational topics such as headcount planning, resource allocation, or vendor/contractor (TVC) tracking (Preferred).
Fluency in English, Mandarin or French is a plus (Preferred).
Benefits
Learn and grow through multiple cutting-edge projects
Flexible work hours and remote work model
Competitive benefits package and competitive total compensation
An additional day off for your birthday
Significant discount on your Montreal transit pass
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.
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