Senior Data Analyst, Compliance

🕒 October 23

🌐 United States, Canada, +1 more countries – Remote

🇺🇸 United States – Remote 🇨🇦 Canada – Remote 🇧🇷 Brazil – Remote

💵 $110.4k - $220.8k / year

⏰ Full Time

🟠 Senior

📉 Data Analyst

👻 Ghost score 4%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Kraken Digital Asset Exchange

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2011

₿ Crypto

💸 Finance

💳 Fintech

Crypto • Finance • Fintech

Kraken Digital Asset Exchange is a cryptocurrency platform that facilitates the buying and selling of over 200 cryptocurrencies, including Bitcoin, Ethereum, and many others. Founded in 2011, Kraken provides a comprehensive suite of features for both beginner and advanced traders, such as advanced trading interfaces and margin trading. The platform emphasizes industry-leading security, deep liquidity, and 24/7 customer support, making it a trusted choice for users worldwide. Kraken caters to individual investors as well as institutional clients, offering services like OTC trading and custody. The company is committed to transparency with its proof of reserves and mission-driven values. Kraken operates globally, supporting clients in over 190 countries, with a quarterly trading volume exceeding $207 billion. However, users are advised of the high risk of crypto investments and the lack of regulation in some jurisdictions.

📋 Description

• Own the logic and rule-setting behind transaction monitoring across deposits and withdrawals • Partner with Compliance to study patterns and refine detection logic • Translate compliance requirements into production detection logic • Preserve 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 proposed-change impact • Design reproducible historical-data evaluations accounting for limited labels, class imbalance, and customer-behaviour shifts • Own testing, deployment, scheduling, monitoring, and operational support for detection workflows • Investigate data quality issues, pipeline failures, and unexpected changes in detection results • Execute historical backfills with clear validation and traceability • Maintain reliable downstream alert delivery and integrations with compliance systems • Experiment, test hypotheses, translate insights into action, and apply software engineering best practices to pipelines and dashboards

🎯 Requirements

• 7+ years of experience in data analysis, data science, and data management within fintech, crypto, financial services, or gambling • Experience working with compliance, fraud, funding, finance, and customer support teams • Experience analyzing large datasets, engineering features, and applying statistical methods • Strong Python and SQL skills • Experience building and supporting production data or analytical systems • Hands-on experience with dbt or similar tooling • Experience setting up and managing data pipelines • Understanding of workflow orchestration • Software engineering practices including version control, automated testing, code review, and CI/CD • Solid statistical foundation • Proficiency with BI and data visualization tools such as Hex, Tableau, Power BI, or similar • Ability to investigate production issues independently and communicate technical findings and uncertainty to non-technical stakeholders • Degree in analytics, software engineering, statistics, economics, or another field emphasizing analytical rigor • Based in Canada, the US, or Brazil • Fluent in English • Experience with fraud detection, AML, anomaly detection, or other risk applications is a nice-to-have • Experience with Athena, Trino, Kafka, Kubernetes, Airflow, dbt, and S3 is a nice-to-have • Experience with transaction pattern analysis, customer segmentation, and detection threshold tuning is a nice-to-have • Experience developing or productionising machine learning models is a nice-to-have • Experience evaluating detection with sparse or delayed investigation feedback is a nice-to-have • Experience with explainability, auditability, and change control in regulated environments is a nice-to-have

🏖️ Benefits

• Bonus program • Equity program • Wellness allowance • Medical insurance • Dental insurance • Vision insurance • 401(k) • Job-related skills or work-style assessments as part of the hiring process • Equal opportunity employment

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