Manager, People Analytics

About the role

The Workplace Engineering function sits at the intersection of traditional HR analytics and modern Product Engineering to transform workforce data into People Products. This role leads a specialized squad of data scientists, software engineers, and designers to drive high performance through predictive and prescriptive insights. You will bridge the gap between technical engineering and human behavioral intent to build the future of the People Data stack.

Responsibilities

• Lead and mentor a specialized squad of People Data Scientists, Software Engineers, and UX Designers.
• Bridge the gap between HR-speak and Dev-speak to ensure engineers understand human behavioral intent.
• Move beyond descriptive metrics to predictive and prescriptive insights.
• Act as the Translator-in-Chief to turn complex data models into compelling narratives.
• Lead the development of AI Agents that surface insights to managers in real-time.
• Ensure the People Data Stack is secure, GDPR/privacy-compliant, and acts as a single source of truth.
• Identify opportunities to leverage high-tech solutions to maximize human value.

Required skills

• Data science
• Mathematics
• Engineering
• Advanced statistics
• Data wrangling
• SQL
• Python
• R
• JavaScript
• Software engineering
• Data visualization
• Automation

Nice to have

• Airbyte
• Ranger
• Superset
• Temporal
• Trino
• Docker
• Kubernetes
• Agentic Engineering
• Product management
• User experience design

Qualifications

• Background in data science, mathematics, or engineering
• Exceptional academic track record

Benefits

• Personal learning and development budget
• Bi-annual compensation review
• Company recognition rewards
• 40 days annual leave
• Maternity and paternity leave
• Team Member Assistance Program
• Wellness Platform
• Priority Pass for lounge access

About the Company

Canonical is a pioneering tech firm at the forefront of the global move to open source. Our platform, Ubuntu, is widely used in breakthrough enterprise initiatives such as public cloud, data science, AI, engineering innovation, and IoT. We are founder-led, profitable, and growing with a distributed work environment.