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Card Fraud Analyst Jobs in California (NOW HIRING)

Sunbit

Analytics Manager, Credit Cards

Los Angeles, CA · On-site +1

Must have 4+ years supporting Credit Card portfolios, with deep experience in Credit Risk, Portfolio Management, Fraud Analytics, or Consumer Lending. * 4+ years of working with and proficient in SQL ...

Collectorsuniverse

Head of Fraud Operations

Santa Ana, CA · On-site +1

$139K - $200K/yr

Our subsidiaries include PSA, PCGS, Beckett, SGC, and Card Ladder. Since our founding in 1986, we ... Manage review-queue health, decision SLAs, and analyst productivity and quality. Investigations ...

PlayStation Global

Payments Analyst

San Diego, CA · On-site

As part of the broader Global Payments and Fraud Management organization, we partner cross ... Familiarity with the card-not-present (CNP) payments ecosystem, including subscription billing ...

JPL

Purchase Card (P-Card) Administrator

Pasadena, CA · On-site

$21.75 - $29.50/hr

The ideal candidate is analytical, organized, and experienced in financial or purchasing ... Coordinate with banking partners on fraud investigations or lost/stolen cards * Maximizing rebate ...

PlayStation Global

Payments Analyst

San Diego, CA · On-site

$110K - $165K/yr

As part of the broader Global Payments and Fraud Management organization, we partner cross ... Familiarity with the card-not-present (CNP) payments ecosystem, including subscription billing ...

Cardless

Data Analyst

San Francisco, CA · On-site +1

$130K - $200K/yr

... card platform ... In this role, you'll work across domains including applications, accounts, transactions, fraud ...

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Card Fraud Analyst information

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How much do card fraud analyst jobs pay per hour?

As of Sep 6, 2026, the average hourly pay for card fraud analyst in California is $30.28, according to ZipRecruiter salary data. Most workers in this role earn between $20.87 and $33.46 per hour, depending on experience, location, and employer.

What does a card fraud analyst do?

A Card Fraud Analyst is responsible for detecting and investigating suspicious or unauthorized credit and debit card transactions. They monitor account activity to identify potential fraud, analyze patterns, and work with banking systems to prevent financial losses. When fraud is suspected, they may contact customers to verify transactions and coordinate with law enforcement or other financial institutions. Their work helps protect both the bank and its customers from fraudulent activities. Strong analytical skills and attention to detail are essential in this role.

What are the key skills and qualifications needed to thrive as a card fraud analyst, and why are they important?

To thrive as a Card Fraud Analyst, you need strong analytical abilities, attention to detail, and a background in finance, business, or a related field. Familiarity with fraud detection software, data analysis tools like SQL, and relevant certifications such as Certified Fraud Examiner (CFE) are highly valued. Outstanding problem-solving, communication, and decision-making skills set top performers apart in this role. These competencies are crucial for accurately detecting fraudulent activity, minimizing financial losses, and ensuring customer trust in banking services.

How do card fraud analysts typically collaborate with other departments to prevent and address fraudulent activity?

Card Fraud Analysts work closely with teams such as customer service, IT, and risk management to quickly identify and respond to suspicious transactions. Collaboration often involves sharing real-time alerts, investigating flagged accounts, and developing new fraud detection strategies. Analysts may also participate in cross-functional meetings to improve security protocols and provide training on emerging fraud trends. This teamwork ensures a coordinated approach to protecting customers and minimizing financial losses.

How much does a card fraud analyst get paid?

A card fraud analyst's average salary typically ranges from $45,000 to $70,000 per year, depending on experience, location, and employer. Entry-level positions may start lower, while experienced analysts with certifications can earn higher salaries, often working with fraud detection tools and data analysis software.

How much does a card fraud analyst make?

A card fraud analyst typically earns between $45,000 and $70,000 annually, depending on experience, location, and employer. Entry-level positions may start lower, while experienced analysts with certifications can earn higher salaries. The role often requires knowledge of fraud detection tools and analytical skills.

What qualifications do you need to be a Card Fraud Analyst?

A Card Fraud Analyst typically needs a bachelor's degree in finance, criminal justice, or a related field. Relevant skills include knowledge of banking systems, fraud detection tools, and strong analytical abilities; certifications such as Certified Fraud Examiner (CFE) can also be beneficial. Prior experience in banking, security, or customer service may be required depending on the employer.

What are popular job titles related to Card Fraud Analyst jobs in California?

For Card Fraud Analyst jobs in California, the most frequently searched job titles are:

What job categories do people searching Card Fraud Analyst jobs in California look for?

The top searched job categories for Card Fraud Analyst jobs in California are:

What cities in California are hiring for Card Fraud Analyst jobs?

Cities in California with the most Card Fraud Analyst job openings:

Card Fraud Analyst jobs near you
Infographic showing various Card Fraud Analyst job openings in California as of August 2026, with employment types broken down into 1% As Needed, 77% Full Time, 18% Part Time, and 4% Contract. Highlights an 97% Physical, 1% Hybrid, and 2% Remote job distribution, with an average salary of $62,987 per year, or $30.3 per hour.

Fraud Strategy Manager / Senior Manager (Onboarding)

Cardless, Inc

San Francisco, CA • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 6 days ago

Job description

At Cardless, we're building a credit card and loyalty platform that consumer businesses use to engage their customers. We've launched 14 credit cards, including for Coinbase, Alibaba, and Qatar Airways. We help businesses bring imaginative card programs to life, and have pioneered technology to embed credit card features natively into their products.
We value curiosity, humility, and intensity - we move fast and take ownership. This is a place where a motivated, resourceful individual can have an enormous impact on our trajectory. We're headquartered in San Francisco, and have raised about $90M in equity funding from top venture capital firms and angels.
The Job
We're looking for a Fraud Strategy Manager or Senior Manager - Onboarding to own the end-to-end fraud strategy for how we evaluate new applicants. This is a highly analytical, strategy-forward role focused on building the decisioning framework that determines which applicants are approved, stepped up for review, or declined, and making sure the tools, data, and processes behind those decisions are best-in-class.
Reporting to our Chief Risk Officer, you'll work at the intersection of data, tooling, and operations to sharpen our onboarding defenses as Cardless scales in the next year. You'll own the manual review program, drive the strategy for leveraging alternative data signals from bank data, device intelligence, and partner sources, and build the measurement infrastructure to continuously improve performance.
What You'll Own
Manual Review Strategy & Operations
  • Define the logic and thresholds for routing applicants into manual review, balancing fraud risk against approval rates and customer experience.
  • Own the manual review program end-to-end: queue prioritization, SLA design, analyst tooling, and case escalation paths.
  • Evaluate the effectiveness of tools used in manual review; identify gaps and advocate for new capabilities that help analysts make faster, higher-quality decisions.
  • Track manual review outcomes rigorously: analyst decisions, approval/decline rates, reversal rates, downstream fraud on reviewed accounts, and false positive costs.
  • Build structured feedback loops between review outcomes and upstream rules triggers to drive continuous policy refinement.

Alternative Data & Signal Development
  • Lead the strategy for incorporating bank account data into onboarding decisions, leveraging signals such as account tenure, balance history, income patterns, and return/NSF activity.
  • Operationalize device intelligence and behavioral signals to strengthen identity and fraud detection at the top of the funnel.
  • Develop a framework for using partner data: loyalty engagement, transaction history, tenure signals as supplementary fraud indicators in co-brand card programs.
  • Evaluate new data sources and vendors on an ongoing basis; build a rigorous test-and-learn methodology to validate signal lift before production deployment.

Fraud Detection & Rules Ownership
  • Own the fraud rules framework for onboarding: design, test, implement, and continuously tune rules across identity, velocity, device, funding, and behavioral dimensions.
  • Partner with data science to define feature requirements, evaluate model performance, and translate model outputs into operational policy.
  • Document all policy decisions clearly, including the tradeoffs made at each threshold.

Performance Measurement & Portfolio Monitoring
  • Define and own the KPI framework for onboarding fraud: fraud rate by vintage and partner, manual review rate, auto-decisioned bad rate, tool efficacy, and cost-per-review.
  • Conduct regular portfolio reviews to surface emerging fraud patterns, track loss trends, and assess detection performance.
  • Build reporting to enable real-time monitoring, trend identification, and rapid policy response.

Cross-Functional Partnership
  • Partner with Product and Engineering to translate fraud strategy into system requirements and influence roadmap prioritization.
  • Work with Compliance and Legal to ensure onboarding controls meet BSA/AML, Red Flags Rule, ECOA, and UDAAP requirements.
  • Collaborate with Customer Operations to manage edge cases, decision appeals, and applicant escalations.

What We're Looking For
  • 5-10 years of experience in fraud strategy, identity risk, or credit risk at a financial institution, fintech, or payments company.
  • Deep expertise in onboarding fraud - synthetic identities, identity manipulation, first-party fraud vectors, and deposit/funding fraud.
  • Hands-on experience with bank data providers in a fraud or credit risk context.
  • Familiarity with device intelligence and behavioral fraud platforms.
  • Strong SQL skills and experience using data to build and evaluate fraud rules, track performance, and identify emerging patterns.
  • Excellent communication skills - you can translate complex fraud tradeoffs into clear recommendations for executives, partners, and compliance teams.
  • Proactive, bias-to-action mindset: you ask the right questions, align stakeholders, and drive decisions forward.

Compensation
This role has an annual starting salary range of $150,000 - $210,000 + equity + benefits (see below). Actual compensation is influenced by a wide array of factors, including but not limited to skills, experience, and specific work location.
Benefits
We're headquartered in San Francisco, CA, with a beautiful office in the Mission District. We're proud to offer our team excellent benefits:
Meaningful Start-up equity
100% health, vision & dental primary coverage
+ 75% health, vision & dental dependent coverage
Catered lunches
$250/month Commuter benefit
Parental leave
Team building events & happy hours
Flexible PTO with a minimum of 15 days off per year
Apple equipment
401k plan
Location
We're headquartered in San Francisco, CA, with a beautiful office in the Financial District. We welcome employees who want to work from this office; we offer additional benefits to those who do, and relocation assistance to those who'd like to.
We regularly bring our team together for offsites & trips, about every 2 months, both for fun and for work. We cover all travel & lodging in these cases.

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