Data Analyst, Risk and Operational Performance
KrakenCanadaPosted 7 April 2026
Job Description
Data Analyst, Risk and Operational Performance
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 https://www.kraken.com/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 https://support.kraken.com/hc/en-us/articles/226090548-How-to-create-an-account-on-Kraken.
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 https://blog.kraken.com/crypto-education/security-at-kraken, crypto education https://blog.kraken.com/category/crypto-education, and world-class client support https://blog.kraken.com/crypto-education/support-at-kraken through our products like Kraken Pro https://pro.kraken.com/, Desktop https://www.kraken.com/desktop, Wallet https://www.kraken.com/wallet, and Kraken Futures https://www.kraken.com/features/futures.
Become a Krakenite and build the future of crypto!
PROOF OF WORK
THE TEAM
At 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 OPPORTUNITY
- Act as a trusted business advisor to the Core Service team, proactively identifying trends and driving efficiency improvements
- Own the design of dashboards, metrics, and reports, turning data into actionable insights for the fraud, funding, risk and support experience teams
- Dive into large, complex datasets/logs to turn your findings into scalable data models necessary to facilitate reporting, analytics and ML models
- Lead cross-functional projects with analysts, scientists, engineers, and product teams to build data pipelines using Airflow, Python, and DBT
- Develop and automate reporting of key performance indicators across core services teams
- Be 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 practices
SKILLS YOU SHOULD ... (truncated, view full listing at source)
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