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Credit Card Risk Management Jobs in California (NOW HIRING)

SoFi

Senior Credit Manager

San Francisco, CA

... Card, and Mortgage) - including credit strategies/policies for new account origination and portfolio management, collections/recovery strategies and operations, and risk and operational data science ...

SoFi

Senior Credit Manager

San Francisco, CA · On-site

... Card, and Mortgage) - including credit strategies/policies for new account origination and portfolio management, collections/recovery strategies and operations, and risk and operational data science ...

Block

Senior Credit Risk Analyst

Bodega Bay, CA · On-site

The Role We're seeking a Senior Credit Risk Analyst to join our Enterprise Risk Management team. This role sits at the intersection of credit risk analytics, data science, and strategic risk ...

Valley Bank

Credit Risk Manager

Los Angeles, CA · On-site

... management. Identifies, outlines, and mitigates risks associated with potential lending ... Ensures credits are accurately risk rated and are properly monitored and reported. * Prepares all ...

Meriwest Credit Union

Card Services Supervisor

San Jose, CA · On-site

$20.25 - $27.75/hr

Card Services Operations • Oversee daily processing of debit/credit card operations including ... Compliance & Risk Management • Ensure adherence to internal policies and regulatory requirements ...

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Credit Card Risk Management information

What is the difference between Credit Card Risk Management vs Credit Analyst?

AspectCredit Card Risk ManagementCredit Analyst
Primary FocusManaging risks associated with credit card portfoliosAssessing creditworthiness of individual borrowers
Work EnvironmentFinancial institutions, credit card companiesBanks, lending institutions
Required CredentialsFinance, risk management certifications often preferredFinance, accounting degrees, certifications like CFA

Credit Card Risk Management focuses on overseeing and mitigating risks related to credit card portfolios, while Credit Analysts evaluate individual credit applications. Both roles require financial knowledge and analytical skills, but their scope and daily tasks differ significantly.

What are some common challenges faced in Credit Card Risk Management roles, and how can they be addressed?

Professionals in Credit Card Risk Management often navigate challenges such as staying ahead of evolving fraud tactics, balancing risk controls with customer experience, and adapting to regulatory changes. Addressing these requires continuous learning, leveraging advanced data analytics, and maintaining strong communication with compliance, IT, and customer service teams. Proactively collaborating with cross-functional departments helps ensure that risk policies are both effective and customer-friendly, while regular training on new fraud trends keeps teams prepared.

What is credit card risk management?

Credit card risk management is the process of identifying, assessing, and mitigating risks associated with issuing and managing credit cards. This includes evaluating the creditworthiness of applicants, monitoring accounts for signs of fraud or default, and implementing policies to minimize financial losses for the credit card issuer. Professionals in this field use data analysis, risk modeling, and regulatory guidelines to ensure responsible lending and maintain the financial health of credit card portfolios.

What are the key skills and qualifications needed to thrive in Credit Card Risk Management, and why are they important?

To thrive in Credit Card Risk Management, you need strong analytical skills, knowledge of financial regulations, and experience with credit risk assessment, often supported by a degree in finance, economics, or a related field. Familiarity with risk modeling software, data analytics tools (such as SAS or SQL), and regulatory compliance systems is typically required. Attention to detail, critical thinking, and effective communication are important soft skills for making sound judgments and collaborating with cross-functional teams. These competencies are essential for identifying, mitigating, and managing potential credit risks to protect the financial health of the organization.
What are popular job titles related to Credit Card Risk Management jobs in California? For Credit Card Risk Management jobs in California, the most frequently searched job titles are:
What job categories do people searching Credit Card Risk Management jobs in California look for? The top searched job categories for Credit Card Risk Management jobs in California are:
Credit Card Risk Management jobs near you
Infographic showing various Credit Card Risk Management job openings in California as of June 2026, with employment types broken down into 87% Full Time, and 13% Part Time. Highlights an 66% In-person, 7% Hybrid, and 27% Remote job distribution.

Engagement Manager - Credit Risk Strategy

Inizio Partners

San Francisco, CA

$160K - $180K/yr

Full-time

Posted 26 days ago

Job description

Role: Engagement Manager - Credit Risk Strategy

Location: Bay Area

Type: Hybrid (2-3 days from office)

Roles & Responsibilities

As a Senior Risk Strategy Leader, you will lead the design and execution of enterprise-scale, data-driven financial risk and fraud strategies across money movement products. You will own strategic risk policy direction and oversee the end-to-end policy lifecycle — from opportunity identification and hypothesis development to testing, deployment, monitoring, and optimization — leveraging large-scale data to balance risk mitigation, customer experience, and sustainable business growth. You will serve as a strategic partner to senior leadership and collaborate cross-functionally to drive scalable risk solutions and respond to critical business and risk events.

  • Lead the development and execution of financial risk and fraud strategies supporting key business initiatives and rapidly evolving risk environments
  • Provide strategic oversight during high-severity and time-sensitive risk incidents, driving coordinated response and mitigation actions
  • Leverage advanced analytics, statistical modelling, and deep domain expertise to design scalable risk frameworks using large-scale transactional and account-level data
  • Own and optimize the end-to-end risk strategy and policy lifecycle: opportunity identification, strategy design, experimentation, deployment, governance, monitoring, and continuous improvement
  • Drive portfolio-level risk management strategies across underwriting, fraud, credit, and money movement products while balancing risk, growth, and customer experience objectives
  • Partner with senior stakeholders across Data Science, Risk Operations, Product, Engineering,
  • Finance, Compliance, and Analytics teams to influence strategic decisions and business outcomes
  • Lead segmentation strategy development, portfolio analytics, and performance deep dives to identify emerging risks and growth opportunities
  • Design and refine underwriting frameworks, credit limits, eligibility policies, and customer risk segmentation strategies
  • Establish scalable monitoring frameworks and governance processes to proactively manage portfolio trends, concentration risks, and segment-level performance
  • Drive hypothesis-led innovation and experimentation to improve approval rates, reduce losses, and enhance operational efficiency
  • Mentor and guide junior analysts and strategy team members, fostering analytical excellence and strategic thinking across the organization
  • Communicate complex analytical insights and strategic recommendations effectively to executive leadership and cross-functional stakeholders

Key Business Problems / Use Cases:

  • Enterprise-scale underwriting, credit policy, and eligibility strategy optimization
  • Portfolio risk management, concentration risk assessment, and performance monitoring across customer segments
  • Fraud strategy design and money movement risk mitigation across payment ecosystems
  • Financial loss forecasting, behavioural modelling, and risk-adjusted growth optimization using payments, card/ACH, and account-level data
  • Hypothesis-driven strategy development and experimentation to improve customer outcomes and portfolio profitability
  • End-to-end risk policy lifecycle management: strategy design experimentation deployment governance optimization
  • Scenario modelling and impact assessment for new products, market expansions, and policy changes
  • Cross-functional strategic planning to balance growth, operational efficiency, compliance, and risk exposure
  • Extensive experience in risk strategy, credit policy, underwriting, fraud strategy, or financial analytics within financial services or fintech environments
  • Proven track record of leading large-scale analytical initiatives and influencing strategic business decisions
  • Strong expertise in leveraging large datasets and advanced analytical techniques to solve complex business and risk problems
  • Advanced proficiency in SQL and Python for analytics, modelling, and strategy implementation
  • Deep experience in statistical modelling, forecasting, risk analytics, and experimental design
  • Strong business acumen with the ability to translate complex analytical insights into actionable strategic recommendations
  • Excellent executive communication, stakeholder management, and cross-functional leadership skills
  • Experience operating in fast-paced, high-growth, and highly regulated environments
  • Demonstrated ability to mentor teams, drive collaboration, and influence senior leadership

Candidate Profile:

Preferred Qualifications:

  • Bachelor's degree in quantitative fields such as Data Science, Statistics, Mathematics, Economics, Finance, or Engineering
  • Master's degree or MBA in a quantitative or business discipline preferred
  • Experience in financial services, fintech, banking, payments, or risk management domains
  • Exposure to money movement products, payment ecosystems, fraud operations, or lending platforms
  • Experience building scalable risk frameworks, governance models, and automated decisioning systems
  • Familiarity with modern data platforms, BI tools, and large-scale experimentation frameworks