OKX
Senior Data Scientist, Compliance Technology
Job Summary
This role involves leading governance, oversight, and validation of transaction monitoring models for fiat and crypto transactions, with a focus on blockchain analytics and DeFi risks. The senior manager will develop strategies to improve model explainability, data pipelines, and typology coverage, collaborating with cross-functional teams. Experience in AML, model validation, and regulatory compliance is essential, along with proficiency in programming and data management. The position offers the opportunity to shape the firm's compliance technology roadmap within a rapidly evolving industry landscape.
Required Skills
Benefits
Job Description
Who We Are
OKX is a leading crypto exchange, and the developer of OKX Wallet, giving millions access to crypto trading and decentralized crypto applications (dApps). OKX is also a trusted brand by hundreds of large institutions seeking access to crypto markets. We are safe and reliable, backed by our Proof of Reserves.
Across our multiple offices globally, we are united by our core principles: We Before Me, Do the Right Thing, and Get Things Done. These shared values drive our culture, shape our processes, and foster a friendly, rewarding, and diverse environment for every OK-er.
About the Opportunity
What You’ll Be Doing
- Design, test, and independently validate rule-based and machine learning models for transaction monitoring, customer risk scoring, sanctions and watchlist screening, and typology detection for both fiat and crypto transactions
- Build and optimize scalable data pipelines integrating blockchain analytics, on-chain and off-chain transaction data, and third-party intelligence tools to enhance risk detection
- Develop and execute robust testing strategies to assess model fitness, typology coverage, Type I and Type II error rates, and regulatory defensibility
- Design strategies to automate monitoring frameworks for model performance, data quality, and risk typology drift; implement advanced analytics to detect anomalies and continuously tune models
- Lead the development and execution of comprehensive metrics and data reporting frameworks, ensuring the accuracy, consistency, and timeliness of key risk indicators, model performance metrics, and regulatory reporting requirements across all FCC models
- Build reproducible and production-ready notebooks, scripts, and workflows following best practices in version control, code testing, and documentation
- Leverage advanced anomaly detection techniques, clustering, and graph analytics to identify emerging financial crime typologies across large multi-source datasets
- Conduct deep-dive data investigations, develop new detection typologies, and translate FCC risk scenarios into effective, explainable models and analytics
- Partner with Product and Engineering to drive enhancements to compliance data architecture, including streaming pipelines, data integrations, and advanced analytics capabilities
- Lead remediation of data quality and model coverage gaps by executing data audits and root cause analysis; maintain thorough documentation and audit trails for regulatory readiness
- Deploy containerized data science workflows and collaborate with engineering teams to integrate models seamlessly into production environments (e.g., using Docker, Kubernetes, or cloud pipelines)
- Contribute to developing reusable data science tools, libraries, or model templates that improve the speed and consistency of future compliance analytics work
- Stay current on regulatory expectations and industry best practices for model governance, validation, and development (NYDFS, FATF, HKMA, MAS, FCA, etc.)
- Produce clear, actionable reports and data visualizations to communicate findings to technical and non-technical stakeholders
- Proactively research and experiment with new open-source tools and techniques that could enhance our FCC model governance and analytics capability
What We Look For In You
- 7+ years of hands-on experience in data science, machine learning, or advanced analytics, ideally in the FCC, AML, KYC, or fraud detection domain
- Proven experience building and validating data models using programming languages such as Python, SQL, Java, R, or similar
- Strong skills in data engineering, large-scale data pipelines, ETL/ELT processes, and streaming analytics (Spark, Kafka, Snowflake, or equivalent)
- Familiarity with blockchain analytics tools (e.g., Chainalysis, TRM Labs, Elliptic) and understanding of on-chain transaction monitoring is highly desirable
- Experience with building, tuning, and monitoring rule-based and ML models for financial crime detection, risk scoring, or sanctions screening
- Solid background in building and maintaining scalable data pipelines, streaming analytics, and working with large, complex datasets
- Experience deploying models into production environments, working with containerization (e.g., Docker, Kubernetes) and cloud data tools
- Solid understanding of typology detection, false positive/negative tuning, and regulatory model validation expectations
- Strong background in data visualization and reporting using BI tools (Tableau, Looker, Power BI, or similar)
- Excellent communication skills to present complex technical findings and recommendations to diverse stakeholders
- Proven ability to work independently in a fast-paced, cross-functional environment
Perks & Benefits
- Competitive total compensation package
- L&D programs and Education subsidy for employees' growth and development
- Various team building programs and company events
- Comprehensive healthcare schemes for employees and dependants
- More that we love to tell you along the process!
- The salary range for this position is $143,000- $257,000
- The salary offered depends on a variety of factors, including job-related knowledge, skills, experience, and market location. In addition to the salary, a performance bonus and long-term incentives may be provided as part of the compensation package, as well as a full range of medical, financial, and/or other benefits, dependent on the position offered. Applicants should apply via OKX internal or external careers site.
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OKX
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