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Financial Crime Risk Investigator Jobs in California

flex.one

Financial Crime Analyst

San Francisco, CA · On-site

$60K - $80K/yr

Draft clear, well-supported case narratives and escalate higher-risk activity for supervisory ... or a related financial crimes role (internship or co‑op experience considered) * Working ...

Robert Half

AML Investigator

San Ramon, CA · On-site

$23.75 - $27.50/hr

... financial crime risks. * Review account records and supporting documentation to assess whether ... Escalate high-risk matters when warranted and coordinate with internal compliance stakeholders to ...

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Financial Crime Risk Investigator information

What cities in California are hiring for Financial Crime Risk Investigator jobs?

Cities in California with the most Financial Crime Risk Investigator job openings:

Infographic showing various Financial Crime Risk Investigator job openings in California as of June 2026, with employment types broken down into 2% Internship, 7% As Needed, 36% Full Time, 10% Part Time, 10% Temporary, and 35% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution.

Financial Crimes Data Scientist

Pasadena, CA • On-site

East West Bank
Commercial Banking • 1 - 5K employees
Learn more about East West Bankexternal

$100K - $200K/yr

Other

Re-posted 3 days ago

East West Bank rating

7.2

Company rating: 7.2 out of 10

Based on 9 frontline employees who took The Breakroom Quiz

118th of 176 rated banks

Job description

Overview

Financial Crimes Data Scientist specializing in the development, deployment, and optimization of in-house AML and fraud detection models. Leverages machine learning, network analytics, and large-scale financial data to identify emerging threats, enhance detection effectiveness, reduce false positives, and support regulatory compliance across financial crime risk programs.

Responsibilities

A Financial Crimes Data Scientist develops, validates, and deploys advanced analytics and machine learning solutions to detect, prevent, and investigate financial crimes, including money laundering, fraud, sanctions violations, and terrorist financing.

Key Responsibilities
  • Design, build, validate, and deploy in-house detection models for AML, fraud, and other financial crime risks.
  • Develop risk-scoring, anomaly detection, predictive, and network analytics models using internal and external data sources.
  • Create and optimize transaction monitoring scenarios and machine learning-driven alert generation frameworks.
  • Implement model deployment pipelines and production monitoring to ensure effectiveness and regulatory compliance.
  • Conduct feature engineering, model tuning, and performance assessment to improve precision, recall, and operational efficiency.
  • Partner with Compliance, BSA/AML, Fraud, Investigations, and Technology teams to translate emerging risks into scalable detection strategies.
  • Reduce false positives while increasing the identification of high-risk activity and suspicious behavior.
  • Support model governance, validation, documentation, and regulatory examinations.
  • Perform other duties as assigned.
Core Expertise
  • Financial Crime Risk Management
  • AML/BSA Compliance
  • Fraud Analytics
  • Machine Learning & AI
  • Graph and Network Analytics
  • Entity Resolution
  • Transaction Monitoring
  • Model Development & Deployment
  • Python, SQL, Spark, Databricks
  • Cloud Analytics Platforms (Azure/AWS)
Qualifications
  • Programming Skills – knowledge of statistical programming languages like R,Python, and database query languages like SQL, Hive, Pig is desirable. Familiarity with Scala, Java, or C++ is an added advantage.
  • Statistics – Good applied statistical skills, including knowledge of statistical tests, behavior clustering, distributions, regression, maximum likelihood estimators, etc. Proficiency in statistics is essential for data-driven companies.
  • Strong Math Skills (Multivariable Calculus and Linear Algebra) - understanding the fundamentals of Multivariable Calculus and Linear Algebra is important as they form the basis of a lot of predictive performance or algorithm optimization techniques.
  • Data Wrangling – proficiency in handling imperfections in data is an important aspect of a data scientist job description.
  • Experience with Data Visualization Tools like Tableau and Power BI that help to visually encode data
  • Network/Link Analytics
  • Excellent Communication Skills – it is incredibly important to describe findings to a technical and non-technical audience.
  • Strong Software Engineering Background
  • Hands-on experience with data science tools
  • Problem-solving aptitude
  • Analytical mind and great business sense

Applicants must have legal authorization to work in the United States. We do not offer visa sponsorship at this time.

Compensation

The base pay range for this position is USD $100,000.00/Yr. - USD $200,000.00/Yr. Exact offers will be determined based on job-related knowledge, skills, experience, and location.

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