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Xero is seeking a General Manager of Data Science to lead a strategic expansion of its data science, analytics, ML, and AI capabilities across Accounting & Bookkeeping, Small Business, and AI products. This is a newly created role combining strategic product vision with platform thinking across metrics, experimentation, data quality, and governance.
You will translate company-level objectives into strategic sub-objectives across analytics, ML, AI products, and experimentation. You'll lead, mentor, and grow a team of data scientists, analytics engineers, ML engineers, and managers, scaling the function from approximately 12 to 30 people. You'll design team structures and operating models that preserve high throughput across multiple locations and time zones, operating as an AI-native leader who drives how AI changes how data science operates and ships value.
As the primary data partner to Product & Technology, you'll advise C-suite and senior leadership on data utilization, retention strategy, new data domains, and AI investment decisions. You'll represent data science in executive forums and partner with Product, Engineering, Design, Marketing, Commercial, Legal, Privacy, and Risk on strategy, prioritization, and governance.
Key responsibilities include owning AI governance, model risk, data quality, privacy posture, and experimentation integrity across the portfolio; driving behavioral, technical, and cultural standards; owning and improving global hiring practices; and proactively identifying delivery and strategic risks while designing robust organizational processes.
The team co-owns Xero's metrics stack, experimentation strategy, and enterprise data architecture, and builds AI-powered customer experiences including the Jax chatbot and agentic workflows in partnership with Anthropic, OpenAI, and Google.
REQUIREMENTS:
- Ability to act as a proactive self-starter and executive partner, shaping strategic agendas with C-suite and senior leadership, presenting to board-level leadership, and influencing key investment decisions
- Proven ability to manage ambiguity, bring structure to complex cross-functional challenges, sustain throughput across multi-timezone teams, and hold stakeholders accountable
- Skilled in leading managers, coaching leaders into senior roles, developing high-performing teams, and constructively escalating strategic risks
- Experienced in navigating teams through significant scale-ups, operating model transformations, and continuous evolution in fast-paced environments
- Practical experience leveraging frontier-model platforms (Anthropic, OpenAI, Google) to build agentic workflows, chatbots, and AI-powered products, and transforming team operating models using AI workflows
- Substantial experience leading data science, ML, or analytics functions with a proven track record of managing other people leaders across multi-team structures
- Extensive experience building and running enterprise-scale data science functions, AI/ML productionization, AI governance, model risk frameworks, and experimentation integrity
- Deep technical fluency across applied ML, analytics engineering, instrumentation, eventing, and schema governance, with a strong engineering mindset focused on building scalable platforms and reusable architectures
- Prior exposure to SaaS or small business segments with a track record of driving scale, data quality, and privacy compliance
- Technical bachelor's or master's degree (PhDs welcome for applied, high-impact organizational challenges), supported by public thought leadership or open-source contributions in data or AI
- A linear data science career is not required; candidates from analyst, scientist, engineer, or AI/ML-focused backgrounds are welcome
