Sr. Data Analyst, Compliance
At a glance
Senior Data Analysis & BI role at Kraken. Remote, United States · full-time · $110,400–$220,800 base.
dataroles summary, based on the employer's posting.
What you'll do
- Shape deposit and withdrawal monitoring rules with Compliance, using transaction patterns to improve detection
- Convert compliance needs into live detection logic while preserving alert rules, thresholds, customer segments, date windows and duplicate handling
- Create Python and SQL workflows to prepare transaction data, engineer features and run detection
- Assess rules and analytical models for coverage, alert quality, threshold sensitivity and the effects of proposed changes
- Operate detection workflows from testing through deployment, investigating failures, checking historical backfills and maintaining alert delivery
What you bring
- At least seven years in data analysis, data science or data management across fintech, crypto, financial services or gambling
- Strong Python and SQL ability, plus a track record of delivering and maintaining production data systems
- Practical experience with dbt or comparable tools for structuring dependable reporting data
- Experience coordinating data pipelines and applying engineering practices such as version control, automated tests, code review and CI/CD
- A degree in an analytically rigorous area, such as analytics, software engineering or statistics
Who this fits
This senior role suits someone who can evaluate detection results, resolve production issues independently and explain technical findings and uncertainty to non-technical partners. You’ll collaborate closely with Compliance and other business teams. The role is remote and available to people based in the United States, Canada or Brazil who are fluent in English.
From the employer
Building the Future of Open Finance
Payward - the parent company behind Kraken, NinjaTrader, Breakout, xStocks, Payward Services and CF Benchmarks - has spent the last 15 years building one of the most modern and globally accessible financial infrastructure platforms in the industry, built to advance an open, global financial system.
The team
Founded in 2011, Kraken is one of the world's longest-standing crypto platforms, trusted by over 10 million individuals and institutions across the globe. It offers spot trading, margin, futures, staking, and OTC services, with products built for both individual investors and institutional clients.
We're looking for a Sr. Data Analyst, Compliance 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 Compliance team. A core part of this role is owning the logic and rule-setting behind transaction monitoring across deposits and withdrawals. You'll also contribute to experimentation infrastructure, laying the groundwork for future ML and intelligence initiatives.
The opportunity
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.
What you bring
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 working 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
Nice to haves
Fraud detection, AML, anomaly detection, or other risk applications
Experience with Athena, Trino, Kafka, and Kubernetes alongside the core Airflow/dbt/S3 stack
Transaction pattern analysis, customer segmentation, and detection threshold tuning
Developing or productionising machine learning models, including experiment tracking and performance monitoring
Working with sparse or delayed feedback from investigations to evaluate and improve detection
Explainability, auditability, and change control in regulated environments
Unless a specific application deadline is stated in the job posting, applications are accepted on an ongoing basis.
Please note, applicants are permitted to redact or remove information on their resume that identifies age, date of birth, or dates of attendance at or graduation from an educational institution.
We consider qualified applicants with criminal histories for employment on our team, assessing candidates in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance.
Our commitment
Payward is powered by people from around the world and we celebrate the diverse talents, backgrounds, contributions, and unique perspectives that everyone brings to the table. We hire based on merit, seeking out people with the right abilities, knowledge, and skills for the job. We encourage you to apply for roles where you don't fully meet the listed requirements, especially if you're passionate or knowledgeable about crypto.
We may ask candidates to complete job-related skills or work-style assessments as part of our hiring process. These assessments evaluate competencies relevant to the role and are applied consistently across candidates for similar positions. Results are considered alongside experience and interviews, and are not the sole basis for any employment decision.
As an equal opportunity employer, we don't tolerate discrimination or harassment of any kind, whether based on race, ethnicity, age, gender identity, citizenship, religion, sexual orientation, disability, pregnancy, veteran status, or any other protected characteristic as outlined by federal, state, or local laws.
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