ZipRecruiter

Log In

1

Credit Risk Data Science Jobs in Foster City, CA

MoneyLion

Staff Data Scientist - Credit

San Francisco, CA · On-site

$140 - $190/hr

This role is well suited for someone with deep credit risk expertise who can connect underwriting ... Data Science, Engineering, and Go-to-Market teams * Translate lender objectives and credit ...

Found

Senior Data Scientist (Risk)

San Francisco, CA · On-site

$163 - $225/hr

... 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 ...

SoFi

Credit Strategy Manager

San Francisco, CA

... 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 ...

Intuit

Manager 2, AI Science

Mountain View, CA · On-site

... 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

Manager 2, AI Science

Mountain View, CA · On-site

... 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

Manager 2, AI Science

Mountain View, CA · On-site

... 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 ...

Apple

WPC Apple Card Data Scientist

Cupertino, CA · On-site

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 ...

US Bank

Credit Risk Analyst

San Francisco, CA · Hybrid

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 ...

SoFi

Credit Strategy Manager

San Francisco, CA · On-site

... 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 ...

previous pagenext page

Showing results 21-40

All JobsCredit Risk Data Science JobsCredit Risk Data Science Jobs in Foster City, CA

Credit Risk Data Science information

See Foster City, CA salary details

$43.1K

$132.7K

$230.2K

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

As of Aug 18, 2026, the average yearly pay for credit risk data science in Foster City, CA is $132,730.00, according to ZipRecruiter salary data. Most workers in this role earn between $96,200.00 and $163,800.00 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 cities near Foster City, CA are hiring for Credit Risk Data Science jobs?

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

Credit Risk Data Science jobs near you

AI Scientist Consumer Risk & Fraud *** Direct End Client ***

Projas Technologies, LLC

Sunnyvale, CA • On-site

Other

Re-posted 20 days ago

Job description

We re seeking a seasoned AI Scientist to lead the development of advanced fraud detection and credit risk models for next-generation financial products. This role combines deep technical expertise with strategic thinking to build scalable, production-ready AI solutions that safeguard money movement systems and lending platforms.

What You ll Do
  • Own the end-to-end lifecycle of fraud risk models from design and development to deployment and monitoring.
  • Build efficient data pipelines for feature engineering, model training, scoring, and reporting using Python and SQL.
  • Apply cutting-edge machine learning techniques (deep learning, tree-based models, NLP, time series, causal inference) to detect fraud patterns.
  • Collaborate with product, engineering, and risk teams to align models with business objectives and compliance standards.
  • Ensure model fairness, interpretability, and regulatory compliance in all deployments.
  • Research and implement innovative AI/ML approaches to improve detection accuracy and scalability.
  • Contribute to MLOps best practices, including automated retraining, monitoring, and version control.
Required Qualifications
  • Advanced degree (MS/PhD) in Computer Science, Data Science, AI, Statistics, or related field.
  • 6+ years of experience in AI/ML model development and deployment.
  • Strong proficiency in Python and SQL.
  • Expertise in fraud risk modeling, credit risk, and financial transaction systems.
  • Hands-on experience with ML frameworks (TensorFlow, PyTorch) and cloud platforms (AWS or Google Cloud Platform).
  • Deep understanding of model calibration, bias correction, and graph-based fraud detection.
  • Proven ability to design scalable pipelines and work in agile environments.
Preferred Skills
  • Experience with Vertex AI, SageMaker, or similar MLOps platforms.
  • Familiarity with workflow orchestration tools (Apache Airflow).
  • Strong background in A/B testing and statistical experimentation.
Why This Role Matters

You ll be solving complex, high-impact problems that protect customers and enable secure financial transactions. If you thrive in fast-paced environments and love applying AI to real-world challenges, this is your opportunity to make a measurable difference.

AI Scientist, Machine Learning Engineer, Fraud Detection, Credit Risk Modeling, Python, SQL, TensorFlow, PyTorch, Deep Learning, NLP, Time Series Analysis, MLOps, Vertex AI, SageMaker, Apache Airflow, Big Data, Financial Risk, Cloud Computing, AWS, Google Cloud Platform, Data Pipelines, Model Deployment, Risk Analytics, Graph Analysis, Fraud Prevention, Fintech AI, Predictive Modeling, Statistical Analysis, CI/CD, Kubernetes, Data Engineering

Apply