Client Engagement Data Analyst - AI

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Proof of work The team 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.

But this is more than a data role.

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 at scale.

In 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.

This is a role for someone who is equally comfortable designing a data model and presenting a dashboard to a senior stakeholder.

You bridge the gap between operational reality and the data architecture needed to make AI work well on top of it.

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

The opportunity AI Orchestration & Outcome Delivery 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 Data Structure & AI Readiness 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 Reporting & Insights 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, and what that tells us about model efficacy Proactively identify emerging patterns in support data and connect them back to reporting and signal strategy Cross-Functional Translation & Team Uplift Partner closely with senior AI and engineering leaders — learning from them, contributing to what's being built, and being the first to apply new capabilities within CE Act as the connective layer between CE operations, the AI/automation team, and engineering — translating operational data needs into clear technical requirements Champion AI literacy across the CE team — teaching, enabling, and building confidence so that AI becomes part of how everyone works, not just a specialist function Communicate data model changes, tagging updates, and reporting outputs to non-technical stakeholders in plain language Contribute to backlog prioritization by sizing the data readiness requirements of proposed AI and automation initiatives Skills you should HODL 3–5 years of experience in a data analyst, operations analyst, or similar role — ideally within fintech, crypto, or high-volume customer operations Demonstrated experience coordinating AI agents (OpenClaw, LangChain, CrewAI) or building AI-powered workflows to solve real business problems not just prompting tools, but designing systems that drive outcomes A proven track record of setting up the data foundations, structures, and governance that allow AI to actually work — understanding that the blocker is rarely the model, it's the data feeding it Strong SQL skills and comfort querying and transforming data across complex systems Hands-on experience with Zendesk or a comparable CX/case management platform — understanding of data structures, ticket fields, tags, and reporting Proficiency with BI tools such as Looker, Mixpanel, or similar — able to build and own dashboards independently Experience designing or contributing to data taxonomy, tagging frameworks, or classification systems Ability to translate between operational language and technical/data requirements — comfortable working with both frontline teams and engineers Familiarity with how AI/ML systems consume structured data — understanding of what "model-ready" data looks like in practice A genuine desire to teach and uplift others — this person raises the AI capability of everyone around them Nice to haves Exposure to AI tagging pipelines, LLM-based classification, or RAG-based knowledge systems Experience with Python or scripting for data transformation and automation Background in crypto, digital assets, or compliance-adjacent operations Familiarity with process mining tools or workflow automation platforms (e.g. n8n, Zapier, Make) Lean Six Sigma or similar process improvement certification Unless a specific application deadline is stated in the job posting, applications are accepted on an ongoing basis.

Please note, applicants are permitted to redact or remove information on their resume that identifies age, date of birth, or dates of attendance at or graduation from an educational institution.

We consider qualified applicants with criminal histories for employment on our team, assessing candidates in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance.

Kraken is powered by people from around the world and we celebrate all Krakenites for their diverse talents, backgrounds, contributions and unique perspectives.

We hire strictly based on merit, meaning we seek out the candidates with the right abilities, knowledge, and skills considered the most suitable for the job.

We encourage you to apply for roles where you don't fully meet the listed requirements, especially if you're passionate or knowledgable about crypto!

We may ask candidates to complete job-related skills or work-style assessments as part of our hiring process.

These assessments are designed to evaluate competencies relevant to the role and are applied consistently across candidates for similar positions.

Assessment results are considered alongside other relevant information, such as experience and interviews, and are not the sole basis for any employment decision.

As an equal opportunity employer, we don’t tolerate discrimination or harassment of any kind.

Whether that’s based on race, ethnicity, age, gender identity, citizenship, religion, sexual orientation, disability, pregnancy, veteran status or any other protected characteristic as outlined by federal, state or local laws.

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