Manager People Analytics

About the Role

Canonical is seeking a Manager People Analytics to join its team in Riyadh, Saudi Arabia. This full-time role is situated within the Workplace Engineering function, which operates at the intersection of HR analytics and Product Engineering. The position reports directly to the Global Head of Workplace Engineering, within the Data discipline of the People department.

Role Context and Purpose

The Workplace Engineering function transforms workforce data into "People Products" designed to enhance performance. This role moves beyond traditional reporting to engineer tools and insights that influence future outcomes. Experienced data professionals at Canonical integrate software, data, and business objectives to transform analytical artifacts into strategic assets, elevating decision-making and innovation across global operations, including sales, marketing, engineering, and human resources. They balance technical precision with business pragmatism, developing experiments, automations, and products that convert insights into tangible outcomes. The role also contributes to shaping the future of the AI/Data stack in open source.

Key Responsibilities

• Lead and mentor a specialized squad comprising People Data Scientists, Software Engineers, and UX Designers, functioning as a product squad leader.
• Serve as Product Owner for People Science initiatives, translating human behavioral intent for engineering teams.
• Develop strategic insights and drive business outcomes by moving beyond descriptive metrics to predictive and prescriptive analytics, such as forecasting attrition risk based on engagement data.
• Act as a "Translator-in-Chief," converting complex data models into clear narratives and leading the development of AI Agents for real-time insight delivery to managers.
• Ensure the People Data Stack is secure, compliant with GDPR and privacy regulations, and serves as a single source of truth for all People-related offerings.
• Identify opportunities to integrate high-tech solutions into People offerings to optimize human involvement and maximize value.

Required Qualifications and Skills

• A background in data science, mathematics, or engineering, with proficiency in advanced statistics, data wrangling/science, databases (SQL), or software engineering.
• Strong skills in coding/scripting languages (Python, R, JavaScript), software engineering, data visualization (*, Superset, Tableau), and automation.
• Ability to translate business questions into key research objectives and identify appropriate methodologies for execution, synthesis, and analysis of findings.
• Proven ability to lead and guide teams to execute against planned roadmaps, demonstrating a strong mentor/coaching mindset.
• Willingness to challenge the status quo and maintain resilience in the face of challenges.
• Ambition to contribute to the development of tomorrow's AI/Data stack in open source.
• An exceptional academic record from high school and university.
• Business-level written and spoken English.
• Sincere personal motivation aligned with Canonical's mission.
• Availability for international travel 2-4 times a year for company events, each up to two weeks long.
• Experience required: 5-10 years.

About Canonical

Canonical is a technology firm recognized for its contributions to open source. Its platform, Ubuntu, is widely used in enterprise initiatives such as public cloud, data science, AI, engineering innovation, and IoT. The company serves leading public cloud and silicon providers, as well as industry leaders across various sectors. Canonical is founder-led, profitable, and expanding. Operating with a globally distributed collaboration model since 2004, Canonical maintains no central headquarters, with most colleagues working remotely. The company emphasizes high expectations and a commitment to excellence, fostering an environment that encourages continuous learning and development.

Equal Opportunity Employer

Canonical is an equal opportunity employer committed to fostering a workplace free from discrimination. The company values diversity of experience, perspectives, and background, recognizing their contribution to a better work environment and improved products. All applications receive fair consideration regardless of identity.