Sr. Data Analyst, Compliance

About this role

Own data pipelines, detection logic, and analytical workflows supporting transaction monitoring for deposits and withdrawals. Partner with Compliance to evaluate and improve detection rules, troubleshoot production issues, and turn analysis into actionable decisions.

About the company

Kraken is a leading cryptocurrency exchange that provides a platform for buying, selling, and trading a diverse range of digital assets. The company focuses on compliance, security, and innovative financial solutions to serve both individual and institutional clients.

The team

Data Analytics

Stack

What you'll do

• Define and refine transaction-monitoring rules with Compliance partners.
• Translate compliance requirements into production detection logic, including thresholds, segmentation, time windows, and deduplication.
• Build and maintain Python and SQL pipelines for transaction data, features, and detection workflows.
• Evaluate detection coverage, alert quality, threshold sensitivity, and proposed rule changes.
• Run reproducible historical evaluations that account for limited labels, class imbalance, and changing customer behavior.
• Own testing, deployment, scheduling, monitoring, and support for detection workflows.
• Perform validated, traceable backfills and maintain downstream alert delivery and system integrations.

What we're looking for

• 7+ years of data analysis, data science, or data management experience in fintech, crypto, financial services, or gambling.
• Strong Python and SQL skills, including production data or analytical systems.
• Experience with dbt or similar data-modeling tools and workflow orchestration.
• Experience with version control, automated testing, code review, and CI/CD.
• Strong statistical foundation and experience analyzing large datasets and engineering features.
• Proficiency with BI tools for executive-facing dashboards.
• Able to investigate production issues and explain technical findings and uncertainty to non-technical stakeholders.
• Based in Canada, the US, or Brazil; fluent in English.

Nice to have

• Fraud detection, AML, anomaly detection, or other risk experience.
• Transaction pattern analysis, customer segmentation, and detection-threshold tuning.
• Experience with Athena, Trino, Kafka, Kubernetes, Airflow, or S3.
• Production machine-learning experience, including experiment tracking and performance monitoring.
• Experience improving detection with sparse or delayed investigation feedback.
• Experience with explainability, auditability, and change control in regulated environments.