Senior Data Analyst transforming scientific and operational data into KPI insights for Sutherland Healthcare Solutions. Leading analytics requirements, testing, and data solutions for life - science research services.
About the role
- Data Analyst focusing on AI in hardware manufacturing for Spherea Group. Analyzing data to modernize workflows and improve manufacturing quality and reliability.
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.
- 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.
- 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 English, Mandarin or French is a plus.
Benefits
- 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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