Job description

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. Stay connected Follow us on Twitter twitter.com Learn on the Kraken Blog blog.kraken.com Connect on LinkedIn linkedin.com Candidate Privacy Notice kraken.com

Requirements

Must-haves

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.
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

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.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

mlpythonsqlci/cdkubernetesmachine learning

Platform: ashby
Effort: quick

Benefits

Benefits detected in the listing.

Pto