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Hourly Credit Risk Modeling Jobs in California (NOW HIRING)

You will own credit risk modeling for our consumer lending and fast-money products, and you will lead the expansion of our fraud modeling program - across three business verticals: Banking, Workforce ...

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Hourly Credit Risk Modeling information

What is hourly credit risk modeling?

Hourly credit risk modeling is the process of assessing and predicting the likelihood of a borrower defaulting on their financial obligations, with risk evaluated and updated on an hourly basis. This approach is often used by financial institutions and fintech companies that require real-time credit risk analysis for instant lending decisions or ongoing portfolio monitoring. By utilizing real-time data and advanced analytics, hourly credit risk modeling enables lenders to respond quickly to changes in a borrower's financial behavior or external market conditions. This leads to more accurate risk assessments and helps institutions manage their exposure more effectively.

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

AspectHourly Credit Risk ModelingCredit Analyst
Primary FocusDeveloping and implementing credit risk models to assess borrower riskAnalyzing credit data to evaluate creditworthiness of individuals or companies
Required SkillsStatistical analysis, modeling, programming, financial analysisFinancial analysis, credit report review, communication skills
Work EnvironmentFinancial institutions, consulting firms, often project-basedBanks, lending institutions, credit departments
CertificationsOften requires CFA, FRM, or similar certificationsTypically requires finance or accounting degrees; certifications like CFA are common

Hourly Credit Risk Modeling involves creating quantitative models to predict credit risk, often requiring advanced statistical and programming skills. Credit Analysts focus on evaluating individual credit data to make lending decisions. While both roles require financial knowledge and may share certifications, their core responsibilities differ: one is model development, the other is credit evaluation.

What are the key skills and qualifications needed to thrive as an hourly credit risk modeler, and why are they important?

To thrive as an Hourly Credit Risk Modeler, you need strong quantitative skills, a background in finance, economics, mathematics, or statistics, and experience with credit risk principles. Familiarity with statistical software such as SAS, R, or Python, as well as knowledge of risk modeling frameworks and regulatory requirements, is typically required. Analytical thinking, attention to detail, and effective communication are crucial soft skills for interpreting data and presenting findings to stakeholders. These skills are essential for accurately assessing credit risk, supporting sound decision-making, and ensuring regulatory compliance in financial institutions.

How does an hourly credit risk modeling professional typically collaborate with other departments within a financial institution?

Hourly Credit Risk Modeling professionals often work closely with teams such as underwriting, data analytics, and IT to ensure credit risk models are accurate and actionable. They may participate in cross-functional meetings to discuss model performance, share insights from data analysis, and implement feedback from business stakeholders. Collaboration is key, as their models directly influence lending decisions, risk management strategies, and regulatory compliance. Regular communication with colleagues helps ensure that risk models stay aligned with evolving business needs and regulatory requirements.

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 Hourly Credit Risk Modeling jobs in California?

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

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

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

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

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

Manager 2, AI Science

Intuit

Mountain View, CA • On-site

Full-time

Posted 8 days ago


Intuit rating

8.2

Company rating: 8.2 out of 10

Based on 92 frontline employees who took The Breakroom Quiz

106th of 244 rated software companies


Job description

Intuit's Consumer Group, including TurboTax and Credit Karma, empowers millions of individuals to take control of their finances. By harnessing the power of data and artificial intelligence (AI), we continuously innovate across consumer lending, banking, and money-movement products to deliver greater value and to protect our members and our platform from risk.


As we expand our Consumer Risk AI Science charter, Intuit Credit Karma is looking for an experienced, hands-on player-coach to join us as a Manager 2, AI Science. In this role you will lead and grow a team of AI scientists who build, deploy, and monitor credit risk and fraud risk AI/ML models that directly affect hundreds of thousands of customers - while staying close enough to the technical work to set a high bar, unblock the team, and personally drive the most complex, ambiguous modeling problems. You will own credit risk modeling for our consumer lending and fast-money products, and you will lead the expansion of our fraud modeling program - across three business verticals: Banking, Workforce Wallet (WFS), and CK Invest. You will partner with the broader Consumer Risk leadership team to set strategy, drive delivery, and develop talent.


Responsibilities

Team & Delivery Leadership

  • Lead, coach, and grow a team of AI scientists 

  • Set the modeling strategy  - owning accountability for the design, development, deployment, and monitoring of credit risk and fraud risk models; set technical direction, review the team's work, remove blockers, and share ownership of program-level success and key results.

  • Direct the team's data strategy - governing the sourcing and use of internal and third-party data such as credit bureau (Experian, TransUnion, Lexis Nexis), cashflow transaction (Plaid, Nova Credit), identity and fraud (Socure, Emailage, ID Analytics) and Intuit tax data - to build proprietary risk attributes and models.

  • Own credit risk AI science for the consumer lending and fast-money portfolio - including first-generation and next-generation credit risk underwriting, cashflow-based underwriting, behavioral, and targeting / eligibility models - for short-term lending products (e.g., tax refund advances, BNPL, installment loans, line of credit, and early wage access).

  • Lead fraud AI/ML modeling across three verticals - Banking, Workforce Wallet (WFS), and CK Invest - owning the fraud model roadmap and its integration into real-time and batch decisioning across the full fraud lifecycle: onboarding, money-in, money-out and account takeover (ATO) fraud.

  • Own the end-to-end model lifecycle - across cloud infrastructure on Intuit AWS (SageMaker, Redshift, Databricks) and CK GCP Vertex AI

  • Own model governance and regulatory compliance (SR 11-7, FCRA, ECOA), including fair lending reviews, adverse action reason codes, and periodic performance reporting to partner banks and internal governance.

  • Partner with Credit and Fraud Policy, Product, Engineering, Legal & Compliance, Model Validation, and partner banks (WebBank, MVB) to embed models into decisioning and to shape risk solutions at the earliest stages of every product launch.

  • Communicate team progress, model impact, and roadmap to senior Risk and Business leadership through regular updates, deep dives, and executive reviews.

  • Lead hiring for the AI Science organization - conducting interviews, representing the modeling function on cross-team panels, and onboarding new employees - and sponsor knowledge-sharing sessions and adoption of modern AI tooling to increase team velocity and productivity.

  • Champion a culture of Agentic AI adoption while guiding the team to design, build, and deploy AI agents and orchestration workflows that automate the end-to-end model development lifecycle-data exploration, feature engineering, validation, training, evaluation, and monitoring-to accelerate team velocity and productivity.

What's great about the role


  • Solve hard, meaningful problems - protecting customers and their hard-earned money while helping them access credit - alongside fun, smart people.

  • Own a broad, high-impact charter spanning credit and fraud across three growing verticals (Banking, Workforce Wallet, and CK Invest).

  • Experience professional growth and encourage growth throughout the team.

  • Work cross-functionally (with executives, engineering, policy & rules, product, analytics, operations, and other AI science teams) to make an immediate, substantial, and sustainable impact.


Qualifications

Minimum Requirements


  • Advanced degree (Ph.D. / MS) in Computer Science, Data Science, AI, Mathematics, Statistics, Econometrics, Physics, or a related quantitative discipline (or equivalent experience).

  • 8+ years of experience in AI Science / Machine Learning, including 2+ years leading or managing AI science / data science teams that have successfully delivered data-driven products.

  • Authoritative knowledge of Python and SQL.

  • Relevant fintech experience in credit risk and/or fraud risk modeling, with a deep understanding of payment systems, money movement, banking, and lending.

  • Hands-on expertise developing, deploying, monitoring and maintaining a variety of machine learning techniques, including but not limited to, deep learning (transformers, sequence modeling), tree-based models, reinforcement learning, clustering, time series, causal analysis, and natural language processing.  

  • Experience leveraging credit bureau, tax, cashflow, identity, and device/behavioral data in risk model development.


Footer

Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position may be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit: Careers | Benefits). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender. 

The expected base pay range for this position is:
Mountain View $237,500 - $321,500
Employment Type: Full-Time

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