Manager, People Analytics

Accountabilities • Lead and mentor a multidisciplinary product squad comprising People Data Scientists, Software Engineers, and UX Designers.

• Own the development of people analytics products that transform workforce data into strategic insights and practical business outcomes. • Bridge people science, business requirements, and software engineering by translating human and organizational objectives into clear technical and research priorities. • Move beyond descriptive reporting toward predictive and prescriptive analytics, including identifying patterns and signals that can inform workforce decisions. • Translate complex data models, research findings, and analytical outputs into clear, compelling narratives for business leaders and managers. • Guide the development of AI-powered tools and agents capable of surfacing relevant workforce insights in a timely and accessible way. • Establish and maintain strong data stewardship practices, ensuring that People data is secure, reliable, privacy-conscious, and compliant with applicable requirements such as GDPR. • Help develop a trusted People Data ecosystem that provides consistent, high-quality information across People-related products and services. • Identify opportunities to use technology and automation to improve workplace effectiveness while creating more capacity for high-value human interactions. • Build and execute strategic roadmaps, ensuring teams are aligned, supported, and able to deliver high-quality outcomes. • Promote data literacy, responsible data use, experimentation, and continuous improvement across the wider organization.

Requirements

• Academic background in data science, mathematics, engineering, or another quantitatively focused discipline, with strong foundations in statistics and analytical methods. • Demonstrated experience with data science, data wrangling, databases, SQL, software engineering, or related technical disciplines. • Strong coding or scripting capabilities in languages such as Python, R, JavaScript, or comparable technologies. • Experience with data visualization and analytics platforms such as Superset, Tableau, or similar tools. • Ability to translate ambiguous business questions into clearly defined research objectives and select appropriate analytical or research methodologies. • Proven ability to synthesize complex findings and communicate them effectively to technical and non-technical audiences. • Demonstrated leadership experience, including managing, mentoring, coaching, and motivating multidisciplinary technical professionals. • Strong product mindset and the ability to develop and execute well-structured roadmaps. • Curiosity, adaptability, resilience, and willingness to challenge established approaches and explore new technologies. • Strong interest in AI, data platforms, automation, and open-source technologies. • Excellent written and spoken English with strong communication and presentation skills. • High standards for precision, reliability, accessibility, collaboration, and quality. • Strong personal accountability, self-motivation, and commitment to delivering meaningful outcomes. • Experience with dbt, Airbyte, Ranger, Superset, Temporal, or Trino is an advantage. • Familiarity with Docker, Kubernetes, agentic engineering, product management, or UX and design is a plus. • Willingness to travel internationally approximately 2–4 times per year for company events lasting up to two weeks.