ZipRecruiter

Log In

1

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

Brigit

Lead Data Scientist

San Francisco, CA · On-site

$185K - $225K/yr

Identifying credit risk of customers so that we can help more people in need when they need it ... Advanced degree in data science, statistics, computer science, or related field. * Proven expertise ...

Mudflap

Senior Data Scientist, Risk

Palo Alto, CA · On-site

$185K - $225K/yr

... mitigate credit and fraud risk across our platform. You'll lead the development of underwriting ... Drive strategic data science initiatives that directly impact business outcomes, working closely ...

Achieve

Data Scientist (AHL)

San Mateo, CA · On-site

$140K - $160K/yr

Serve as a strategic thought partner for other members of the Data Science team Qualifications What ... Experience with credit risk modeling (development & monitoring) and loss/prepayment forecasting.

Achieve

Data Scientist (AHL)

San Mateo, CA

Serve as a strategic thought partner for other members of the Data Science team Qualifications What ... Experience with credit risk modeling (development & monitoring) and loss/prepayment forecasting.

Gusto, Inc.

Data Scientist, Risk

San Francisco, CA

$186K - $230K/yr

Here's what we're looking for: * 7-10 years of experience in Data Science at a product-focused software company. * Experience with Risk DS and risk modeling. * Strong SQL skills and comfort with ...

Brigit

Senior Data Scientist

San Francisco, CA · On-site

$175K - $200K/yr

Identifying the credit risk of customers so that we can help more people in need when they need it ... Advanced degree in data science, statistics, computer science, or related field. * Proven expertise ...

US Bank

Credit Policy Manager

San Francisco, CA · On-site

Vision | We create the future of credit risk management through data, analytics, and risk process innovation for our customers. Mission | We deliver data-driven information solutions to protect our ...

Monitise

Data Scientist

Sunnyvale, CA · On-site

$104K - $160K/yr

Any time you swipe your credit card, pay through a mobile app, or withdraw money from the bank, w ... The Risk Analysts in EPayments are the data scientists responsible for the identification of fraud ...

Gusto, Inc.

Data Scientist, Risk

San Francisco, CA · On-site

$186K - $230K/yr

Here's what we're looking for: * 7-10 years of experience in Data Science at a product-focused software company. * Experience with Risk DS and risk modeling. * Strong SQL skills and comfort with ...

Canadian Solar

Credit Controller

Walnut Creek, CA · On-site

Key Responsibilities Credit Risk & Portfolio Management * Lead the Company's credit risk and ... data analytics, and scalable business practices. * Foster collaborative relationships across ...

Canadian Solar

Credit Controller

Walnut Creek, CA · On-site

Key Responsibilities Credit Risk & Portfolio Management * Lead the Company's credit risk and ... data analytics, and scalable business practices. * Foster collaborative relationships across ...

SoFi

Senior Manager, Data Science

San Francisco, CA · On-site

... risk, legal, compliance, and executive teams to set business objectives, define product strategy ... Manage a team of Data Scientists supporting SoFi's Checking and Savings, Invest, Credit Card ...

previous page

Showing results 41-60

All JobsCredit Risk Data Science JobsCredit Risk Data Science Jobs in Fremont, CA

Credit Risk Data Science information

See Fremont, CA salary details

$40.5K

$124.7K

$216.2K

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

As of Aug 6, 2026, the average yearly pay for credit risk data science in Fremont, CA is $124,662.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,300.00 and $153,800.00 per year, depending on experience, location, and employer.

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 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.
What are popular job titles related to Credit Risk Data Science jobs in Fremont, CA? For Credit Risk Data Science jobs in Fremont, CA, the most frequently searched job titles are:
What job categories do people searching Credit Risk Data Science jobs in Fremont, CA look for? The top searched job categories for Credit Risk Data Science jobs in Fremont, CA are:
What cities near Fremont, CA are hiring for Credit Risk Data Science jobs? Cities near Fremont, CA with the most Credit Risk Data Science job openings:
Credit Risk Data Science jobs near you
Infographic showing various Credit Risk Data Science job openings in Fremont, CA as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $124,662 per year, or $59.9 per hour.

Data Scientist, AI Solutions

DataVisor

Mountain View, CA • On-site

Full-time

Medical, Dental, Vision, Retirement

Re-posted 28 days ago

Job description

DataVisor is the world’s leading AI-powered Fraud and Risk Platform that delivers the best overall detection coverage in the industry. With an open SaaS platform that supports easy consolidation and enrichment of any data, DataVisor's fraud and anti-money laundering (AML) solutions scale infinitely and enable organizations to act on fast-evolving fraud and money laundering activities in real time. Its patented unsupervised machine learning technology, advanced device intelligence, powerful decision engine, and investigation tools work together to provide significant performance lift from day one. DataVisor's platform is architected to support multiple use cases across different business units flexibly, dramatically lowering total cost of ownership, compared to legacy point solutions. DataVisor is recognized as an industry leader and has been adopted by many Fortune 500 companies across the globe.

Our award-winning software platform is powered by a team of world-class experts in big data, machine learning, security, and scalable infrastructure. Our culture is open, positive, collaborative, and results-driven. Come join us!

Role Summary

We are seeking a hands-on Data Scientist to serve as the "Architect of Efficacy" for our AI-Powered Fraud and AML Solutions suite. In this role, you will move beyond simple analysis to build the mathematical core of our product. You will design pre-built detection strategies that provide immediate protection for new clients, solving the industry-wide "Cold Start" problem. Working at the intersection of research and product, you will collaborate closely with our Product, Strategy, Data Science, Delivery, and Engineering teams to translate complex fraud patterns into scalable, automated defenses.

Responsibilities
  • Develop Pre-Built Detection Models: Design, back-test, and optimize statistical baselines and machine learning strategies for our core solution modules, including Real-Time Payments (RTP), ACH, Wire, Check, and Application/Onboarding.
  • Mine the Global Consortium: Analyze large-scale, cross-industry data within our global intelligence network to identify high-risk device fingerprints and patterns of organized fraud, transforming these insights into features that can be deployed across all clients.
  • Architect "Cold Start" Logic: Create generalized scoring models that deliver immediate value to new clients, ensuring they are protected against known threats even before their historical data is fully integrated.
  • Validate AI Agent Logic: Serve as the expert "Human-in-the-Loop" for our AI-driven strategy engine, rigorously testing and validating automated fraud detection logic to ensure safety, transparency, and low false positive rates.
  • Cross-Functional R&D: Collaborate with Product, Strategy, Data Science, Delivery, and Engineering teams to explore and implement state-of-the-art machine learning and large language model (LLM) capabilities, providing the statistical rigor needed to turn experimental concepts into production-grade features.

Requirements

Qualifications
  • Education: MS or MS in Computer Science, Statistics, Mathematics, Engineering, or a related discipline.
  • Experience: Minimum 1 year of hands-on experience in Data Science or Advanced Analytics.
  • Technical Core: Proficiency in Python (Pandas, NumPy, Scikit-learn) and SQL.
  • Statistical Rigor: Solid foundation in statistical modeling, feature selection, and performance evaluation (Precision/Recall, AUC, KS).
Preferred Qualifications
  • Experience with graph theory or link analysis for detecting network-based fraud.
  • Familiarity with unsupervised learning techniques or anomaly detection.
  • Previous experience working in a high-growth SaaS or Fintech environment.
  • Domain Knowledge: Familiarity with Fraud Detection, Credit Risk, or Trust & Safety, including knowledge of payment rails (FedNow, ACH, Wire) and typologies (Synthetic ID, ATO, Kiting).

Benefits

  • Salary ranges between USD 120,000 and 170,000.
  • Total compensation includes base salary, performance bonuses, and equity options.
  • Comprehensive medical, dental, and vision insurance coverage.
  • 401(k) retirement savings plan available.
  • Flexible Time Off (FTO) plus paid holidays.
  • Opportunities for research, development, and professional advancement.
  • Regular team-building events in a collaborative and innovative work environment.