Experience and Qualifications:

Technical Foundation:

- 8+ years of experience in data science or analytics roles, with readiness to take on coordination and leadership responsibilities

- Strong experience with Python and SQL for data analysis and solution development

- Good experience with cloud platforms (e.g. GCP, Azure, AWS) and cloud-based analytics tools

- Solid understanding of data science methods, statistical approaches, and their practical application in commercial contexts

- Familiarity with analytics and delivery best practices, and interest in helping others apply them

AI-Native Capability:

- Transformation across a portfolio. You've driven AI adoption or workflow change across a set of assets or a team's ways of working, with targets and tracking. You can describe what you set out to change, what actually moved, and what stalled

- Still hands-on. Active, current use of AI coding and analytics tools such as Claude, Claude Code, Cursor, or GitHub Copilot, to the point where you can sit with a senior engineer, look at their agent setup, and have a useful opinion

- Working understanding of how multi-step agentic workflows are built, evaluated, and maintained: context design, tool definitions, evaluation loops, failure recovery, and human checkpoints

- Awareness of what agentic pipelines cost to run and maintain, including token spend, run time, and review burden, and the point at which automation costs more than it saves

- Ability to frame AI capability to senior stakeholders in outcome terms such as cycle time, capacity released, quality, and risk, rather than tool adoption counts

Readiness for Management:

- Interest in supporting and developing others (formal management experience is welcome but not required)

- Good communication and collaboration skills for working with diverse team members across cultures, time zones, and experience levels

- Willingness to learn management skills including goal-setting, feedback, and performance conversations

- Openness to developing your own leadership style with guidance and support

- Comfort holding accountability for outcomes owed to stakeholders in other countries, including escalating and pushing back when needed

Problem-Solving & Adaptability:

- Systematic approach to problem-solving with ability to coordinate complex technical work

- Ability to balance technical involvement with team coordination and AI transformation responsibilities

- Commercial understanding, or willingness to develop the business context behind analytics work

- Adaptability and resilience in a rapidly changing technical environment, particularly comfort with the pace of AI evolution

Education & Background:

- Degree in engineering, mathematics, statistics, computer science, physics, or a related quantitative field, or equivalent demonstrated capability

What Would Be Great to Have:

- Experience mentoring, training, or leading teams - formal or informal

- Coordinate the development of analytics solutions across product initiatives, ensuring quality and consistency in technical approaches

- Retail analytics background, or client-facing consulting experience across other industries (e.g. financial services, government, health)

- Previous exposure to product development environments or cross-functional collaboration

- Experience working across different cultures or in distributed teams

- Understanding of data governance, privacy considerations, and ethical AI practices