Data Scientist, Financial Crimes - USDS

About the role

TikTok USDS Joint Venture LLC is dedicated to the safety and security of millions of Americans who create, discover, and connect with what they love on the apps we operate. The Joint Venture has been established in compliance with the Executive Order signed by President Trump on September 25, 2025. Our foundation is a comprehensive data privacy and cybersecurity program we operate under defined safeguards to protect national security and secure U.S. user data, apps and the algorithm. We safeguard the U.S. content ecosystem, holding decision-making authority for trust and safety policies and moderation. USDS Joint Venture helps ensure Americans can continue to express their creativity, discover new hobbies and interests, and build thriving communities and businesses on a global scale.

Responsibilities

• Develop, implement, and optimize machine learning models to detect money laundering, fraud, and other financial crimes, leveraging techniques such as anomaly detection, clustering, and predictive modeling.
• Analyze large volumes of transactional and user data to identify suspicious patterns or behaviors indicative of financial crimes.
• Perform data analysis to support transaction monitoring, sanction, KYC and high-risk investigation teams, including performing ad-hoc data analysis, that assist Financial Crime Compliance leadership in decision-making and strategic planning processes.
• Design and implement data visualization dashboards and reporting tools to communicate insights and findings from financial crime detection efforts.
• Collaborate with internal stakeholders to design, develop, validate, and implement AML scenarios, and conduct threshold tuning to optimize performance.
• Document and manage projects related to threshold tuning, scenario design, and detection methodologies.
• Collaborate with cross-functional teams, including product, engineering, and operations to integrate machine learning solutions into existing systems and processes.
• Perform special projects, and additional duties and responsibilities as required.

Qualifications

• Master's degree (Ph.D. is a plus) in Statistics, Mathematics, Finance, Computer Science Engineering or a similar Quantitative field, or equivalent practical experience
• 3+ years of experience in data analysis, statistical modeling, machine learning , with a focus on financial crime compliance or related domains.
• Proficiency in programming languages Python, HQL, Neo4J, Spark as well as experience with machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch).
• Experience with data visualization tools and techniques for creating interactive dashboards and reports (e.g., Tableau, Power BI, matplotlib).
• Strong analytical skills and the ability to work with large datasets to extract actionable insights.