Client Engagement Data Analyst - AI

Kraken is a mission-focused company building the future of crypto. Our Krakenites are a world-class team with crypto conviction, united by a desire to discover and unlock the potential of crypto and blockchain technology. As a fully remote company, we have Krakenites in 70+ countries who speak over 50 languages. We are committed to industry-leading security, crypto education, and world-class client support through our products like Kraken Pro, Desktop, Wallet, and Kraken Futures.

We're on a mission to accelerate the global adoption of crypto so that everyone can achieve financial freedom and inclusion.

The Client Engagement Data Analyst - AI sits at the intersection of Client Engagement operations, data infrastructure, and AI capability. This role exists to ensure that the data signals flowing through our support systems are clean, well-structured, and ready to power AI-driven insights and automation.

We are looking for someone who has actually orchestrated AI to solve real business problems — not just someone who uses AI tools, but someone who has built the systems, data foundations, and governance frameworks that allow AI to make good decisions  most organizations, the bottleneck isn't the AI model, it's the quality and structure of the data feeding it. This person knows how to remove that bottleneck.

Working closely with the Process Optimization & Automation Team, you will co-own the logic and governance that shapes how support data is structured, tagged, and interpreted — and translate that structure into meaningful reporting that drives decisions across Client Engagement and beyond. You bridge the gap between operational reality and the data architecture needed to make AI work well on top of it.

Importantly, you bring others along with you — building confidence and capability across the team as AI becomes embedded in how we all work.

• Design and coordinate AI agent workflows that solve real operational problems, going beyond off-the-shelf tools to build systems that actually drive outcomes
• Identify where AI can deliver the most impact within CE operations and take ownership of making those use cases work end-to-end
• Establish the data foundations, tagging logic, and system architecture that allow AI to make accurate, reliable decisions
• Act as the team's first mover — testing, applying, and refining new AI capabilities before they are rolled out broadly

• Design and maintain data models that support AI tagging, classification, and reporting across Client Engagement systems
• Audit and optimize data tables in Zendesk and connected platforms to ensure they are structured for AI consumption
• Define how support data categories, fields, and hierarchies map to desired AI output — working closely with the AI layer owner to ensure inputs are clean, consistent, and model-ready
• Identify gaps between current data structure and what is needed to unlock new AI capabilities

• Build and maintain dashboards and reports that surface AI performance signals, support trends, and operational health metrics
• Develop the Echo Report and other AI-driven reporting outputs that translate raw data into clear client and operational insights
• Monitor the feedback loop between AI outputs and human behavior — tracking when specialists accept, edit, or override AI-suggested categories
• Proactively identify emerging patterns in support data and connect them back to reporting and signal strategy

• Partner closely with senior AI and engineering leaders — learning from them and being the first to apply new capabilities within CE
• Act as the connective layer between CE operations, the…