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Internship Credit Risk Modeling Jobs in California

The Senior Credit Manager will work in the Credit team and have responsibilities to analyze and evaluate data to develop and propose value-added credit risk strategies and models for SoFi's lending ...

The ideal candidate will oversee delivery across multiple strategic client accounts, where our teams work across credit risk strategy, fraud, collections, and model development. The individual needs ...

The Senior Credit Manager will work in the Credit team and have responsibilities to analyze and evaluate data to develop and propose value-added credit risk strategies and models for SoFi's lending ...

The Senior Credit Manager will work in the Credit team and have responsibilities to analyze and evaluate data to develop and propose value-added credit risk strategies and models for SoFi's lending ...

The role as QuickBooks Capital credit risk lead analyst will dive into three main areas to help the ... the latest technology and models to serve our QuickBooks customers' financing needs ...

The role as QuickBooks Capital credit risk lead analyst will dive into three main areas to help the ... the latest technology and models to serve our QuickBooks customers' financing needs ...

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Internship Credit Risk Modeling information

What is an internship in credit risk modeling?

An Internship in Credit Risk Modeling is a temporary position, usually for students or recent graduates, where you work with financial institutions to understand and help develop models that predict the likelihood of borrowers defaulting on loans. Interns typically assist in analyzing data, building statistical models, and supporting risk assessment processes. This role provides hands-on experience with financial data, programming, and model validation, making it valuable for those interested in finance, statistics, or data science. It also offers exposure to regulatory requirements and real-world risk management practices.

What types of projects or tasks can I expect to work on during an internship in credit risk modeling?

As an intern in Credit Risk Modeling, you'll typically assist with statistical analysis, data preparation, and validation of risk models used by the organization to evaluate creditworthiness. You may support senior analysts in building or refining predictive models using programming languages like Python or R, and work with large datasets to uncover trends in borrower behavior. Interns often collaborate with risk analysts, data scientists, and IT teams, gaining exposure to both technical and business perspectives. This hands-on experience helps build a solid foundation for a future career in quantitative finance or risk management.

What are the key skills and qualifications needed to thrive as an internship in credit risk modeling, and why are they important?

To thrive as an Internship Credit Risk Modeling, you generally need strong quantitative and analytical skills, a background in finance, statistics, or a related field, and familiarity with risk concepts. Experience with statistical programming languages such as Python, R, or SAS, and proficiency in Excel or SQL, are commonly required, and relevant coursework or certifications in risk management or data analysis are advantageous. Attention to detail, critical thinking, and effective communication help interns stand out when interpreting data and presenting risk findings. These skills are important to ensure accurate risk assessments, support data-driven decision-making, and facilitate collaboration within financial institutions.

What is the difference between Internship Credit Risk Modeling vs Credit Risk Analyst?

AspectInternship Credit Risk ModelingCredit Risk Analyst
CredentialsTypically pursuing or recent graduate, some familiarity with finance or statisticsBachelor's degree in finance, economics, or related field; often requires some experience
Work EnvironmentInternship setting, supervised, project-basedFull-time, professional environment, more independent responsibilities
Industry UsageEntry-level, educational focus, training periodCore role in financial institutions, ongoing risk assessment

Internship Credit Risk Modeling positions are designed for students or recent graduates gaining initial experience, often with supervised tasks. Credit Risk Analysts are experienced professionals responsible for ongoing risk evaluation, requiring more advanced skills and independence. The internship serves as a training ground, while the analyst role involves continuous risk management in financial institutions.

What are the most commonly searched types of Credit Risk Modeling jobs in California?

The most popular types of Credit Risk Modeling jobs in California are:

What are popular job titles related to Internship Credit Risk Modeling jobs in California?

For Internship Credit Risk Modeling jobs in California, the most frequently searched job titles are:

What job categories do people searching Internship Credit Risk Modeling jobs in California look for?

The top searched job categories for Internship Credit Risk Modeling jobs in California are:

What cities in California are hiring for Internship Credit Risk Modeling jobs?

Cities in California with the most Internship Credit Risk Modeling job openings:

Data Scientist - Credit & Risk

San Francisco, CA • On-site

Full-time

Re-posted yesterday


Job description

Traditional credit was built for people who already have money. Requirements for credit history, collateral, and costly underwriting create insurmountable barriers for those who need capital most. Over 1.4 billion people lack access to credit. A vendor in Lagos earns cash daily but can't prove a steady income. A Colombian nurse with years of perfect informal repayments remains invisible to banks. Most lending systems spend a lot to guess who will repay, and yet so many who are creditworthy still can't get a loan.
We built an alternative called Credit. Since December 2024, it has issued over one million unsecured loans using stablecoins. People from around the world have used these loans to pay for things like groceries, medicine, and transportation. Backed by $6.6 million from Paradigm and Nascent, we're scaling a system that has already reached more than 900,000 unique borrowers. Help us take it to the next level.
About the role
We're looking for a data scientist to drive credit risk intelligence across Credit, our leading unsecured lending system. You'll own portfolio monitoring and reporting, research emerging risk trends, and transform borrower behavioral data into actionable guidance that shapes our credit strategy and roadmap.
While our engineering & research teams owns the underlying models, you'll be the person who makes sense of what they're telling us, tracking portfolio health, identifying issues early, and turning insights into clear recommendations for risk strategy and underwriting policy. Over time, this role may expand to drive broader product analytics across our suite of products.
This role is based in San Francisco, California. We work in a hybrid model, with the team in office 3 days per week.
Stack
  • Python
  • SQL
  • Grafana/Prometheus/Metabase
  • Blockchain data and indexing tools (Dune, Shovel)
Key responsibilities
  • Monitor credit risk models, including underwriting, loss forecasting, and fraud detection, and iterate based on observed portfolio performance
  • Design, build, and maintain scalable data pipelines, monitoring infrastructure, and dashboards to track portfolio health, user behavior, and key risk indicators
  • Partner with product, research, and engineering teams to define north star metrics and translate them into measurable, actionable credit and growth strategies
  • Design and analyze A/B tests, quasi-experiments, and causal inference studies to evaluate the impact of product and policy changes
  • Produce portfolio monitoring and investigative analyses, making recommendations based on findings
  • Translate complex quantitative findings into clear, compelling narratives for product, leadership, and cross-functional stakeholders
Requirements
  • 4+ years of experience in decision science, credit risk analytics, or a closely related quantitative role within fintech or consumer lending
  • Deep proficiency in Python and SQL; comfortable owning analyses end-to-end from raw data to recommendation
  • Strong understanding of credit risk modeling concepts, including PD/LGD modeling, scorecard development, reject inference, vintage analysis, and risk segmentation
  • Demonstrated experience monitoring credit risk metrics and portfolio performance, including loss forecasting and underwriting model improvement
  • Proven ability to influence and collaborate with cross-functional teams and senior stakeholders, with a track record of translating analytical findings into accessible, actionable insights
  • Experience designing and evaluating experiments (A/B tests, holdout groups, or causal inference frameworks) in a consumer product context
  • Comfortable with ambiguity and biased toward action; thrives with minimal oversight and brings strong problem-solving skills and sharp attention to detail
Nice to have
  • Experience building or maintaining large-scale data pipelines supporting B2C financial products
  • Familiarity with credit bureau data, cash flow underwriting, or alternative data sources in credit model development
  • Experience working in emerging markets, ideally on financial products serving everyday consumer needs (microfinance, BNPL, digital lending)
  • Strong understanding of DeFi protocol mechanics (lending, yield vaults, ERC4626) and experience with onchain data tooling (Dune, Shovel, Ponder, Goldsky or similar)
  • Exposure to regulatory frameworks relevant to consumer credit (FCRA, ECOA, or equivalent)

Divine Research is an equal opportunity employer.