Data Analyst, Risk and Operational Performance
KrakenData AnalyticsPosted 24 February 2026
Job Description
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 workThe teamAt Kraken, data is both a strategic asset and the foundation of trust with our users, partners, and stakeholders and the data team is the backbone of decision-making.We’re looking for a Data Analyst, Risk and Operational Performance to join our team remotely! The primary goal of this role is to elevate decision-making by uncovering emerging trends and root causes, and by driving insights and actions that provide full visibility into business performance and operational efficiency.Beyond technical expertise, success in this role depends on being a true business partner who combines data-driven insights with strategic thinking to deliver actionable recommendations, guide decision-making, and drive measurable impact across the organization.In this role, you’ll own end-to-end data management from building and maintaining datasets and pipelines to designing dashboards and delivering insights for the Core Services team. Additionally, you’ll also contribute to experimentation infrastructure and ML initiatives, including launching and evaluating A/B experiments.You will be, quite literally and quantitatively, defining success on a daily basis for our Core Services and other teams across the organization. Join us and be part of a team where data is not just an asset but our language, our tool, and our future!The opportunityAct as a trusted business advisor to the Core Service team, proactively identifying trends and driving efficiency improvementsOwn the design of dashboards, metrics, and reports, turning data into actionable insights for the fraud, funding, risk and support experience teamsDive into large, complex datasets/logs to turn your findings into scalable data models necessary to facilitate reporting, analytics and ML modelsLead cross-functional projects with analysts, scientists, engineers, and product teams to build data pipelines using Airflow, Python, and DBTDevelop and automate reporting of key performance indicators across core services teamsBe at the forefront of data innovation by experimenting, testing hypotheses, and translating insights into action.Develop high-quality code for pipelines and dashboards, incorporating software engineering best practicesSkills you should HODL5+ years of experience in data analysis and data management within the Fintech industry gained in a fast-paced, high-growth environmentExperience working with fraud, funding, finance and customer support teams to analyze and optimize operational performance across the business systemsThis role requires expert SQL skills and hands-on experience in Python Hands-on experience using dbt (data build tool) to model and organize data for reporting and decision-makingExperience setting up and managing data pipelines, ... (truncated, view full listing at source)
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