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Fraud Risk Jobs in California (NOW HIRING)

Avidbank

Fraud Specialist

San Jose, CA · On-site

$65K - $100K/yr

Risk and Compliance - BSA / Fraud Work Location Type: San Jose HQ Office Location: San Jose, California The Role The Fraud Specialist serves as the primary point of contact for all fraud-related ...

Avidbank

Fraud Specialist

San Jose, CA · On-site

Risk and Compliance - BSA / Fraud Work Location Type: San Jose HQ Office Location: San Jose, California The Role The Fraud Specialist serves as the primary point of contact for all fraudrelated ...

TikTok

Fraud Investigator

San Jose, CA · On-site

$121K - $220K/yr

... internal fraud risk by conducting platform monitoring and undertaking deep-dive projects. - Identify any possible threats to company and take appropriate actions to avoid them promptly.

Intuit

Senior Staff Fraud Risk Analyst

Mountain View, CA

$199K - $270K/yr

As a key leader of the Credit Risk Management team for Intuit's business credit card product, this individual will be responsible for developing, optimizing and managing strategies for credit card ...

Intuit

Senior Staff Fraud Risk Analyst

Mountain View, CA · On-site

$199K - $270K/yr

As a key leader of the Credit Risk Management team for Intuit's business credit card product, this individual will be responsible for developing, optimizing and managing strategies for credit card ...

Travis Credit Union

Sr. Risk Analyst

Vacaville, CA · On-site

$98K - $121K/yr

Assesses fraud risk trends and patterns to develop proactive prevention strategies leveraging predictive analytics. * Performs root-cause analysis to identify vulnerabilities in processes or systems.

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Fraud Risk information

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$14

$29

$73

How much do fraud risk jobs pay per hour?

As of Jun 22, 2026, the average hourly pay for fraud risk in California is $29.94, according to ZipRecruiter salary data. Most workers in this role earn between $19.23 and $38.17 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Fraud Risk Analyst, and why are they important?

To thrive as a Fraud Risk Analyst, you need strong analytical skills, attention to detail, and a background in finance, accounting, or a related field, often supported by a relevant degree. Familiarity with fraud detection software, data analytics tools (like SQL, SAS, or Python), and certifications such as Certified Fraud Examiner (CFE) are typically required. Excellent problem-solving, communication, and critical thinking skills help you proactively identify risks and work effectively with cross-functional teams. These abilities are crucial for detecting and mitigating fraudulent activities, protecting organizational assets, and maintaining regulatory compliance.

What is the difference between Fraud Risk vs Fraud Analyst?

AspectFraud RiskFraud Analyst
Required CredentialsRisk management certifications, knowledge of fraud preventionCertifications like CFE, CPA, or fraud examination credentials
Work EnvironmentRisk assessment teams, compliance departmentsInvestigations, data analysis, reporting
Employer & Industry UsageFinancial institutions, insurance, retailBanking, finance, insurance, retail

Fraud Risk focuses on identifying and managing potential vulnerabilities to fraud within an organization, emphasizing risk assessment and mitigation strategies. Fraud Analysts, on the other hand, investigate specific fraud cases, analyze data, and detect fraudulent activities. While both roles require knowledge of fraud prevention, Fraud Risk professionals develop strategies to prevent fraud, whereas Fraud Analysts handle the detection and investigation of actual incidents.

What is fraud risk and what does a fraud risk analyst do?

Fraud risk refers to the possibility that an individual or organization will intentionally deceive others for financial or personal gain. A fraud risk analyst is responsible for identifying, assessing, and mitigating risks related to fraudulent activities within a company or financial institution. Their duties typically include monitoring transactions, analyzing data patterns, developing anti-fraud policies, and working with law enforcement or regulatory agencies to investigate suspicious activities. By proactively managing fraud risk, these professionals help protect their organization’s assets and reputation.

What are some common challenges faced by professionals in Fraud Risk roles, and how can they be addressed?

Professionals in Fraud Risk roles often encounter challenges such as staying ahead of rapidly evolving fraud tactics, managing large volumes of data, and balancing the need for security with customer experience. To address these, it’s crucial to continuously update knowledge on emerging threats, leverage advanced analytical tools, and collaborate closely with IT, compliance, and customer service teams. Regular training, cross-department communication, and investment in technology can help ensure effective fraud detection and prevention while maintaining positive client interactions.
What are the most commonly searched types of Fraud Risk jobs in California? The most popular types of Fraud Risk jobs in California are:
What are popular job titles related to Fraud Risk jobs in California? For Fraud Risk jobs in California, the most frequently searched job titles are:
What job categories do people searching Fraud Risk jobs in California look for? The top searched job categories for Fraud Risk jobs in California are:
Fraud Risk jobs near you
Infographic showing various Fraud Risk job openings in California as of June 2026, with employment types broken down into 5% As Needed, 47% Full Time, 38% Part Time, and 10% Contract. Highlights an 92% Physical, 3% Hybrid, and 5% Remote job distribution, with an average salary of $62,273 per year, or $29.9 per hour.
AI Scientist Consumer Risk & Fraud *** Direct End Client ***

AI Scientist Consumer Risk & Fraud *** Direct End Client ***

Projas Technologies, LLC

Sunnyvale, CA • On-site

Other

Posted 23 days ago

Job description

We re seeking a seasoned AI Scientist to lead the development of advanced fraud detection and credit risk models for next-generation financial products. This role combines deep technical expertise with strategic thinking to build scalable, production-ready AI solutions that safeguard money movement systems and lending platforms.

What You ll Do
  • Own the end-to-end lifecycle of fraud risk models from design and development to deployment and monitoring.
  • Build efficient data pipelines for feature engineering, model training, scoring, and reporting using Python and SQL.
  • Apply cutting-edge machine learning techniques (deep learning, tree-based models, NLP, time series, causal inference) to detect fraud patterns.
  • Collaborate with product, engineering, and risk teams to align models with business objectives and compliance standards.
  • Ensure model fairness, interpretability, and regulatory compliance in all deployments.
  • Research and implement innovative AI/ML approaches to improve detection accuracy and scalability.
  • Contribute to MLOps best practices, including automated retraining, monitoring, and version control.
Required Qualifications
  • Advanced degree (MS/PhD) in Computer Science, Data Science, AI, Statistics, or related field.
  • 6+ years of experience in AI/ML model development and deployment.
  • Strong proficiency in Python and SQL.
  • Expertise in fraud risk modeling, credit risk, and financial transaction systems.
  • Hands-on experience with ML frameworks (TensorFlow, PyTorch) and cloud platforms (AWS or Google Cloud Platform).
  • Deep understanding of model calibration, bias correction, and graph-based fraud detection.
  • Proven ability to design scalable pipelines and work in agile environments.
Preferred Skills
  • Experience with Vertex AI, SageMaker, or similar MLOps platforms.
  • Familiarity with workflow orchestration tools (Apache Airflow).
  • Strong background in A/B testing and statistical experimentation.
Why This Role Matters

You ll be solving complex, high-impact problems that protect customers and enable secure financial transactions. If you thrive in fast-paced environments and love applying AI to real-world challenges, this is your opportunity to make a measurable difference.

AI Scientist, Machine Learning Engineer, Fraud Detection, Credit Risk Modeling, Python, SQL, TensorFlow, PyTorch, Deep Learning, NLP, Time Series Analysis, MLOps, Vertex AI, SageMaker, Apache Airflow, Big Data, Financial Risk, Cloud Computing, AWS, Google Cloud Platform, Data Pipelines, Model Deployment, Risk Analytics, Graph Analysis, Fraud Prevention, Fintech AI, Predictive Modeling, Statistical Analysis, CI/CD, Kubernetes, Data Engineering

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