Financial Crimes Data Scientist

East West Bank is seeking a Financial Crimes Data Scientist to design, implement, and optimize AML and fraud-detection models using machine learning, network analytics, and large-scale financial data. The role concentrates on enhancing detection capabilities, reducing false positives, and supporting regulatory compliance, with an onsite base in Pasadena, California.

Responsibilities

• Develop and deploy internal models to detect AML, fraud, and related financial crime risks, including end-to-end design, validation, and rollout.
• Build risk-scoring, anomaly-detection, predictive, and network-analytics models using both internal and external data sources.
• Create and refine transaction monitoring scenarios and machine learning–driven alerting frameworks.
• Establish model deployment pipelines and ongoing production monitoring to maintain effectiveness and regulatory alignment.
• Perform feature engineering, model tuning, and performance assessments to improve precision, recall, and operational efficiency.
• Collaborate with Compliance, BSA/AML, Fraud, Investigations, and Technology teams to translate evolving risks into scalable detection approaches.
• Aim to minimize false positives while enhancing detection of high-risk activity and suspicious behavior.
• Support governance, validation, documentation, and regulatory examinations of models.
• Perform additional duties as required.

Requirements

• Proficiency in statistical programming languages such as Python or R, and experience with SQL-based data querying (including Hive and Pig) is preferred; familiarity with Scala, Java, or C++ is a plus.
• Strong applied statistics background covering hypothesis testing, clustering behaviors, distributions, regression, and maximum likelihood estimation.
• Solid grounding in multivariable calculus and linear algebra.
• Ability to wrangle imperfect data and prepare clean datasets for analysis.
• Experience with data visualization tools like Tableau and Power BI to effectively encode and present data.
• Experience with network or link analytics.
• Strong communication skills to convey findings to both technical and non-technical audiences.
• Solid software engineering foundation.
• Hands-on experience with data science toolchains and practical implementations.
• Strong problem-solving aptitude and analytical mindset with business acumen.

Technologies

• Python
• SQL
• Spark
• Databricks
• Hive
• Pig
• Scala
• Java
• C++
• Tableau
• Power BI
• Azure
• AWS

Compensation

Base pay range: USD 100,000 - 200,000 per year. Exact offers will be determined based on job-related knowledge, skills, experience, and location.