Responsibilities

About the Team In line with the globalization strategy and vision of the company, the Global Payments Department builds a platform to provide cross-border payment solutions for all ByteDance's products and services, that are growing rapidly worldwide. The compliance solution function under Compliance Team is a global function responsible for building and scaling a best-in-class and end-to-end business and payment compliance solution. About the Role The TikTok Financial Crime Compliance (FCC) organization is dedicated to building a robust, data-driven framework to mitigate risks such as money laundering, terrorist financing, and other financial crimes. This senior analyst role is central to our Model and Data Risk Governance function, responsible for providing independent and authoritative validation of the models and critical data infrastructure that underpin our global FCC controls. As a Senior Model / Data Risk Analyst, you will act as a subject matter expert, ensuring our risk management systems are conceptually sound, technically robust, and performing effectively. You will provide critical assurance to leadership and stakeholders by rigorously testing our models and data pipelines, influencing their design and ongoing enhancement, and upholding the highest standards of regulatory compliance and internal governance. Responsibilities - Independent Model Validation: Conduct comprehensive, independent validations of FCC models (e.g., transaction monitoring, sanctions screening, customer risk rating), assessing conceptual soundness, data integrity, system implementation, and performance. - Data Risk & Lineage Validation: Perform end-to-end data validation, from source-to-target reconciliation to verifying data quality controls (completeness, accuracy, timeliness) and ETL logic within critical compliance data pipelines. - Performance Monitoring & Backtesting: Design and execute a framework for ongoing model performance monitoring, backtesting, and outcome analysis; identify and investigate performance degradation, providing recommendations for remediation. - Challenger Model Development: Develop and maintain challenger models and analytics to benchmark the performance of production models and identify opportunities for enhancement. - Governance & Documentation: Create and maintain detailed validation documentation, including reports, work papers, and findings, suitable for internal stakeholders, auditors, and regulators. - Cross-functional Influence: Collaborate closely with Data Science, Engineering, Product, and AML Operations teams to communicate validation results, drive remediation of identified issues, and provide expert guidance on model and data risk management best practices. - Reporting & Communication: Prepare and present clear, concise reports on validation activities, findings, and model risk posture to senior management and governance committees. - Regulatory Adherence: Stay current with regulatory expectations (e.g., SR 11-7, EU AMLDs, MAS guidelines) and ensure the validation framework and practices align with industry standards.

Qualifications

Minimum Qualifications: - Bachelor’s or higher degree in a quantitative field such as Statistics, Mathematics, Computer Science, Economics, or a related discipline. - 5+ years of experience in model validation, data validation, quantitative analysis, or a similar role within the financial services, FinTech, or regulatory technology sector. - Advanced proficiency in SQL for complex data extraction and analysis. - Hands-on experience with a programming language for data analysis and statistical modeling (e.g., Python, R). - Strong understanding of data warehousing concepts, ETL processes, and big data technologies (e.g., Hive, Spark, Presto). - Foundational knowledge of AML/CFT typologies and experience with compliance systems related to KYC/KYB, transaction monitoring, or sanctions screening. Preferred Qualifications: - Deep expertise in model risk management frameworks and regulatory requirements (e.g., OCC SR 11-7). - Proven experience conducting independent validations of machine learning models and traditional statistical models. - Expertise in designing and implementing data quality frameworks and controls for large-scale data systems. - Experience creating insightful management information (MI) and dashboards using tools like Tableau, Power BI, or similar. - Professional certification such as CAMS (Certified Anti-Money Laundering Specialist) or CFE (Certified Fraud Examiner). - Excellent written and verbal communication skills, with the ability to articulate complex technical concepts to both technical and non-technical audiences. - Demonstrated ability to lead projects, influence cross-functional partners, and operate with a high degree of autonomy and accountability.

Job Information