About the Team

The Global Payment team provides Tik Tok payment solutions -- including payment acquisitions, disbursements, transaction monitoring, payment method management, foreign exchange conversion, accounting, reconciliations, and so on to ensure that our users have a smooth and secure payment experience on the Tik Tok platform. The Global Payment Compliance team, leveraging industry and technological expertise, provides compliance policy, oversight, advisory and operational support to all of our company's products and services.

About the Role

Traditional transaction monitoring is no longer enough. By joining us, you will help build a holistic defense mechanism that catches bad actors not just by how they move money, but by how they behave on our platform. You will define the future of how our company views risk.

We are seeking a specialized Data Analyst to pioneer our cross-platform compliance strategy. In this role, you will look beyond traditional money movement to integrate diverse risk signals-such as Trust & Safety data, user behavior logs, and content moderation flags-into our Financial Crimes Compliance (FCC) ecosystem. You will be responsible for designing the data logic, policies, and referral pathways that ensure high-risk non-financial events are accurately identified and escalated to our investigation teams for regulatory reporting (STR).

Responsibilities

Cross-Platform Data Integration & Analysis

• Analyze complex datasets across disparate platforms, correlating financial transaction data with non-financial signals (e.g., login patterns, device fingerprinting, Trust & Safety violations, marketplace interactions).
• Identify patterns where platform abuse (e.g., fraud, scams, illegal goods) precedes or coincides with money laundering or terrorist financing risks.
• Build data models that trigger alerts based on hybrid indicators (e.g., a user flagged for hate speech who suddenly receives large peer-to-peer transfers).

Policy & Referral Process Development

• Develop and document the logic for "Non-Financial STR Referrals," defining exactly when a Trust & Safety or Marketplace signal should trigger a financial crimes investigation.
• Create Standard Operating Procedures (SOPs) for the intake of cross-platform referrals, ensuring they meet regulatory standards for Suspicious Transaction/Activity Reports.
• Collaborate with Legal and Compliance leadership to calibrate risk thresholds, ensuring we capture true positives without overwhelming investigators with noise.

Pipeline Optimization & Tooling

• Work with Engineering and Product teams to automate the ingestion of T&S signals into the FCC case management system.
• Design dashboards to monitor the volume, quality, and outcome of cross-platform referrals (e.g., conversion rates from T&S referral to STR filing).
• Conduct "below-the-line" testing to tune detection scenarios and reduce false positives.

Strategic Analytics & Insight Delivery

• Drive the design and execution of foundational FCC analytics initiatives. Go beyond routine analysis to uncover emerging risk typologies, assess control effectiveness, and provide data-driven recommendations that directly influence FCC/AML policy, operational strategies, and risk appetite.
• Take ownership of the analytics lifecycle for risk detection. Design, develop, and validate innovative data signals and features from complex, large-scale datasets to enhance our transaction monitoring, sanctions screening, and customer risk rating models.
• Architect and maintain a suite of robust dashboards and automated reports for Management Information (MI) reporting, providing senior leadership with clear visibility into key risk indicators (KRIs), control performance, and trend analysis.

Stakeholder Collaboration

• Act as the primary liaison between the Trust & Safety, Product, and FCC Investigations teams.
• Translate complex data findings into clear policy recommendations for senior leadership.
• Provide training to investigators on how to interpret non-financial data points within a financial crime context.

Qualifications

Minimum Qualifications

• Bachelor's degree or higher in a quantitative field such as Data Science, Statistics, Mathematics, Computer Science, or a related discipline.
• 5+ years of hands-on experience in data analytics, data science, or a similar role, with a significant focus on the financial services, Fin Tech, or regulatory compliance/risk management sectors.
• Advanced proficiency in SQL and demonstrable experience using Python or R for complex data manipulation, statistical analysis, and automation.
• Proven experience working with large-scale data warehousing environments (e.g., Hive, Spark SQL, Presto) and familiarity with ETL principles.
• Solid understanding of core AML/CFT and sanctions compliance domains (e.g., KYC/KYB, Transaction Monitoring, Sanctions Screening).

Preferred Qualifications

• CAMS, CFE, or other relevant professional certification is highly desirable.
• Deep knowledge of major AML regulatory frameworks (e.g., BSA/AML, EU AML Directives, MAS guidelines) and their practical application in a payments or e-commerce context.
• Experience working in multi-product ecosystem (Social Media + Payments).
• Experience in developing or validating AML models and an understanding of model risk management principles.
• Demonstrated ability to lead complex analytical projects from conception to completion and effectively influence cross-functional stakeholders at all levels.
• Exceptional communication and presentation skills, with the ability to translate complex data findings into clear, concise, and compelling narratives for both technical and non-technical audiences.