Remote Senior Data Analyst — Compliance & Detection

The Bitcoin Street Journal; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

Kraken is seeking a Sr. Data Analyst, Compliance to remotely elevate decision-making by uncovering trends and root causes in a fast-paced crypto environment.

You will own end-to-end data management, from building datasets and pipelines to designing dashboards and delivering insights for the Compliance team. You will translate regulatory requirements into production detection logic, refine detection rules, and evaluate models for coverage and alert quality.

Qualifications

• 7+ years of experience in data analysis, data science, and data management within the fintech, crypto, financial services, or gambling industry, gained in a fast-paced, high-growth environment.
• Experience with compliance, fraud, funding, finance, and customer support teams and analyzing large datasets, engineering features, and applying statistical methods to practical business problems.
• Strong Python and SQL skills, with experience building and supporting production data or analytical systems.
• Hands-on experience using dbt or similar tooling to model and organize high-fidelity data for reporting and decision-making.
• Experience setting up and managing data pipelines with a strong understanding of workflow orchestration, plus strong software engineering practices including version control, automated testing, code review, and CI/CD.
• Solid statistical foundation; ML exposure is a strong plus.
• Proficiency with BI and data visualization tools (e.g., Hex, Tableau, Power BI, or similar) to build executive-facing dashboards.
• Ability to investigate production issues independently and communicate technical findings and uncertainty to non-technical stakeholders.
• You believe wholeheartedly in the values outlined in Kraken’s Tentaclements document
• A degree in a field emphasizing analytical rigor, such as analytics, software engineering, statistics, or economics
• Based in Canada, the US, or Brazil, and fluent in English

Responsibilities

• Own the logic and rule-setting behind transaction monitoring across deposits and withdrawals, partnering closely with Compliance to study patterns and refine detection logic.
• Translate compliance requirements into production detection logic, preserving correctness across alert eligibility, thresholds, customer segmentation, date windows, and deduplication.
• Develop and maintain Python and SQL pipelines for transaction data preparation, feature engineering, and detection workflows.
• Evaluate detection rules and analytical models across coverage, alert quality, threshold sensitivity, and the impact of proposed changes.
• Design reproducible evaluations on historical data that account for limited labels, class imbalance, and shifts in customer behaviour over time.
• Own testing, deployment, scheduling, monitoring, and operational support for detection workflows, including investigating data quality issues, pipeline failures, and unexpected changes in detection results.
• Execute historical backfills with clear validation and traceability, and maintain reliable downstream alert delivery and integrations with compliance systems.
• Be at the forefront of data innovation by experimenting, testing hypotheses, and translating insights into action, while incorporating software engineering best practices into pipelines and dashboards.

Skills

Python

SQL

Data analysis

Data science

BI tools

dbt

Pipelines

Stakeholder communication

Education

Analytics/Statistics degree

Tools

Airflow

dbt

Kafka

Kubernetes

Athena

Trino

Tableau

Power BI

Hex

S3

Job description

Kraken is seeking a Sr. Data Analyst, Compliance to remotely elevate decision-making by uncovering trends and root causes in a fast-paced crypto environment.

You will own end-to-end data management, from building datasets and pipelines to designing dashboards and delivering insights for the Compliance team. You will translate regulatory requirements into production detection logic, refine detection rules, and evaluate models for coverage and alert quality.