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$ cat jobs/manager-people-analytics-canonical-ltd-553a1d8a36e2.json

Manager, People Analytics

Canonical Ltd.·Canada·EMEA, LATAM, Canada, USA·mid
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The Workplace Engineering function sits at the intersection of traditional HR analytics and modern Product Engineering. We transform raw workforce data into a suite of "People Products" that drive high performance. We don’t just "report" on what happened; we engineer the tools and insights that determine what happens next. This new role will report directly to the Global Head of Workplace Engineering, and sits within our Data discipline inside of our People department. Experienced data professionals at Canonical live at the intersection of software, data, and the business. They don't just help surface analytic artifacts; they help transform them into a strategic asset that elevates decision making and innovation across our global operations (e.g., sales, marketing, engineering, and human resources). They balance technical precision with business pragmatism, designing and iterating on experiments, automations, and products that transform insights into valued outcomes. They shape tomorrow's AI/Data stack in open source, ensuring that Canonical remains at the forefront of data-driven excellence. Their curiosity is contagious and has an amplifying effect on data literacy and stewardship across the business teams they support. Location: This is a remote role based in the AMER or EMEA Region. The role entails Multi-Disciplinary Leadership: Lead and mentor a specialized squad of People Data Scientists, Software Engineers, and UX Designers. You aren't just managing analysts; you are leading a product squad. Product Ownership on People Science: Bridge the gap between "HR-speak" and "Dev-speak", ensuring engineers understand the human behavioral intent behind the code. Strategic Insight & Business Outcomes: Move beyond descriptive metrics (e.g., turnover rate) to predictive and prescriptive insights (e.g., predicting attrition risk based on "Time-Product" engagement data). Data Stewardship & Product Storytelling: Act as the "Translator-in-Chief". Take complex data models and