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Credit Risk Data Science Jobs in Sunnyvale, CA (NOW HIRING)

Experience applying predictive modeling to credit risk assessment, churn prediction, loss and ... data science productivity, quality, and business impact. The anticipated annual base salary for ...

... credit, fraud, and compliance risks. * Develop and Implement Risk Controls: Partner with product, engineering and data science teams to design, build, and deploy automated risk controls and ...

... and risk and operational data science and analytics. The team designs data-driven strategies to ... The Credit Strategy Lead will work in the Credit team and have responsibilities to analyze and ...

... 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 ...

... 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 ...

You should have experience and subject matter expertise in financial modeling, payments, banking, credit, risk operations, data science, and finance. Previous experience working in the credit card ...

This role will perform data analyses and share results, using such tools as SAS, SQL, Toad, Python ... Risk competencies - Strong process facilitation and project management skills - Effective ...

Showing results 21-40

Credit Risk Data Science information

See Sunnyvale, CA salary details

$43.4K

$133.7K

$231.8K

How much do credit risk data science jobs pay per year?

As of Aug 21, 2026, the average yearly pay for credit risk data science in Sunnyvale, CA is $133,657.00, according to ZipRecruiter salary data. Most workers in this role earn between $96,800.00 and $164,900.00 per year, depending on experience, location, and employer.

What is credit risk data science?

Credit Risk Data Science is a specialized field that uses statistical analysis, machine learning, and data modeling techniques to assess and predict the likelihood that a borrower will default on a loan or credit obligation. Professionals in this field analyze large datasets from financial transactions, credit reports, and market trends to develop models that help financial institutions make informed lending decisions. Their work helps manage risk, set appropriate interest rates, and comply with regulatory standards. By leveraging advanced analytics, credit risk data scientists play a crucial role in minimizing losses and maximizing profitability for banks and lenders.

What skills and qualifications are needed to thrive as a credit risk data scientist?

To thrive as a Credit Risk Data Scientist, you need strong analytical skills, proficiency in statistical modeling, and a solid background in finance, mathematics, or a related field, often supported by an advanced degree. Familiarity with programming languages like Python or R, experience with machine learning frameworks, and knowledge of credit risk modeling tools such as SAS or SQL are typically required. Critical thinking, attention to detail, and effective communication are vital soft skills for interpreting data and collaborating with stakeholders. These abilities are crucial for building accurate risk models, informing strategic decisions, and ensuring regulatory compliance in financial institutions.

How does a credit risk data scientist typically collaborate with other teams within a financial institution?

Credit Risk Data Scientists often work closely with credit analysts, risk managers, and IT professionals to develop, validate, and implement models that assess borrower risk. They frequently participate in cross-functional meetings to translate complex analytical findings into actionable business insights. Collaboration with compliance and regulatory teams is also common to ensure that risk models meet current regulatory standards. Effective communication and teamwork are essential, as the role bridges technical model development and practical risk management decisions.

What are popular job titles related to Credit Risk Data Science jobs in Sunnyvale, CA?

For Credit Risk Data Science jobs in Sunnyvale, CA, the most frequently searched job titles are:

What cities near Sunnyvale, CA are hiring for Credit Risk Data Science jobs?

Cities near Sunnyvale, CA with the most Credit Risk Data Science job openings:

Infographic showing various Credit Risk Data Science job openings in Sunnyvale, CA as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $133,657 per year, or $64.3 per hour.

Credit Risk Strategy Manager / Senior Manager

Cardless, Inc

San Francisco, CA • On-site

$150K - $210K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 19 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 Credit Risk Strategy Manager or Senior Manager to own the credit strategy for managing risk across our existing cardholder portfolio. This is a highly analytical, strategy-forward role focused on building the decisioning framework that determines how we extend additional credit, manage exposure, and optimize portfolio performance as well as ensuring the tools, data, and processes behind those decisions are best-in-class.
Reporting to our Head of Credit, you'll work at the intersection of data, tooling, and operations to optimize customer-level credit decisions as Cardless scales. You'll own the strategy for actions such as credit line increases and decreases, balance transfer offers, and other portfolio management levers, while building the measurement infrastructure needed to continuously improve performance for a rapidly growing portfolio.
What You'll Own
Portfolio Strategy & Signal Development
  • Define the logic and thresholds for credit line increases, decreases, and exposure management - balancing portfolio growth, credit risk, and customer experience
  • Develop the strategy and implementation for new programs such as balance transfers and ongoing spend campaigns
  • Build structured feedback loops between portfolio performance and policy triggers to drive continuous refinement
  • Develop processes for loss forecasting, leading edge delinquencies, and other methods to understand future portfolio performance
  • Build and maintain automated dashboards to track key performance indicators (KPIs) around portfolio performance
  • Design and execute A/B tests to evaluate new strategies, balancing product performance with customer and partner satisfaction

Cross-Functional Partnership
  • Partner with Data Science to define feature requirements, evaluate model performance, and translate model outputs into operational policy
  • Partner with engineering to build and implement new strategies such as proactive credit line increase execution and reactive credit line increase APIs
  • Work with Compliance and Legal to ensure portfolio management policies comply with ECOA, FCRA, Fair Lending, and other applicable regulations
  • Work together with brand partners to balance company and partner goals and share out performance and results
  • Work with bank partners to document, present and get approval for new policies/models

What We're Looking For
  • 5-10 years of experience in credit risk strategy, portfolio management, or underwriting at a financial institution, fintech, or payments company.
  • Deep expertise in consumer credit portfolio management - experience with credit line management, utilization dynamics, and loss forecasting is a plus
  • Experience leveraging behavioral and bureau data to develop/optimize strategies
  • Strong SQL skills and experience using analytics to build and evaluate credit strategies, track portfolio performance, and identify emerging risk patterns.
  • Familiarity working with credit risk models (including regression and tree-based machine learning) and decision engines in a production environment.
  • Excellent communication skills - you can translate complex credit 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.