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Client Engagement Data Analyst - AI
Kraken — топовый работодатель в криптоиндустрии с сильной культурой и полностью удаленным форматом. Позиция находится на острие технологий (AI + Crypto), предлагает работу с современным стеком и реальное влияние на продукт.
Сложность вакансии
Роль требует редкого сочетания навыков: глубокой аналитики данных (SQL, BI) и практического опыта оркестрации ИИ-агентов (LangChain, CrewAI). Высокая планка ответственности за создание инфраструктуры данных для ИИ в глобальной криптобирже делает позицию сложной, но перспективной.
Анализ зарплаты
Указанная роль аналитика данных с фокусом на ИИ в финтех-секторе Бразилии оплачивается выше среднего по рынку из-за специфики криптоиндустрии и требований к навыкам оркестрации ИИ. Рыночные оценки для Senior/Specialist ролей в международных компаниях для этого региона обычно находятся в диапазоне $45,000 - $75,000 в год.
Сопроводительное письмо
I am writing to express my strong interest in the Client Engagement Data Analyst - AI position at Kraken. With a solid background in data orchestration and a proven track record of building AI-powered workflows using frameworks like LangChain, I am excited about the opportunity to bridge the gap between operational data and AI-driven insights within your world-class team.
In my previous experience, I have focused on the critical bottleneck of AI implementation: data quality and structure. I have successfully designed data models and tagging taxonomies that transformed raw support data into 'model-ready' assets, significantly improving the accuracy of automated decision-making. My proficiency in SQL and Looker, combined with a hands-on approach to Zendesk optimization, aligns perfectly with Kraken's mission to accelerate global crypto adoption through superior client engagement.
I am particularly drawn to Kraken’s mission-driven culture and your commitment to financial freedom. I am eager to bring my technical expertise and passion for crypto to help uplift the team's AI literacy and deliver scalable, data-driven solutions that enhance the experience for millions of Krakenites worldwide.
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Описание вакансии
Building the Future of Crypto
Our Krakenites are a world-class team with crypto conviction, united by our desire to discover and unlock the potential of crypto and blockchain technology.
What makes us different?
Kraken is a mission-focused company rooted in crypto values. As a Krakenite, you’ll join us on our mission to accelerate the global adoption of crypto, so that everyone can achieve financial freedom and inclusion. For over a decade, Kraken’s focus on our mission and crypto ethos has attracted many of the most talented crypto experts in the world.
Before you apply, please read the Kraken Culture page to learn more about our internal culture, values, and mission. We also expect candidates to familiarize themselves with the Kraken app. Learn how to create a Kraken account here.
As a fully remote company, we have Krakenites in 70+ countries who speak over 50 languages. Krakenites are industry pioneers who develop premium crypto products for experienced traders, institutions, and newcomers to the space. Kraken is committed to industry-leading security, crypto education, and world-class client support through our products like Kraken Pro, Desktop, Wallet, and Kraken Futures.
Become a Krakenite and build the future of crypto!
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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Навыки
- Python
- LLM
- SQL
- Looker
- RAG
- Zendesk
- Six Sigma
- Data Modeling
- Mixpanel
- LangChain
- CrewAI
- Taxonomy
- OpenClaw
Возможные вопросы на собеседовании
Проверка практического опыта работы с инструментами оркестрации ИИ, указанными в вакансии.
Расскажите о самом сложном ИИ-воркфлоу, который вы спроектировали с использованием LangChain или CrewAI. С какими проблемами в данных вы столкнулись?
Вакансия подчеркивает, что данные — главный барьер для ИИ. Нужно понять подход кандидата к подготовке данных.
Как вы определяете, что данные являются 'model-ready' (готовыми для модели)? Приведите пример трансформации 'грязных' операционных данных в структурированный формат для LLM.
Роль предполагает работу с Zendesk и клиентским опытом.
Каким образом вы бы оптимизировали структуру тегов и полей в Zendesk, чтобы улучшить точность классификации обращений с помощью ИИ?
Проверка навыков визуализации и донесения ценности данных до бизнеса.
Опишите ваш опыт создания дашбордов в Looker или Mixpanel. Какие метрики вы считаете ключевыми для оценки эффективности внедрения ИИ в клиентскую поддержку?
Soft skills и способность обучать команду.
Как вы подходите к объяснению сложных изменений в моделях данных или алгоритмах ИИ нетехническим стейкхолдерам?
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