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

Intuit

Principal Credit Risk Analyst

Mountain View, CA · On-site

$236K - $319K/yr

The role as QuickBooks Capital credit risk lead analyst will dive into three main areas to help the ... Partner with our data science and data engineering teams to leverage the latest technology and ...

Intuit

Principal Credit Risk Analyst

Mountain View, CA · On-site

$236K - $319K/yr

The role as QuickBooks Capital credit risk lead analyst will dive into three main areas to help the ... Partner with our data science and data engineering teams to leverage the latest technology and ...

Intuit

Principal Credit Risk Analyst

Mountain View, CA · On-site

$236K - $319K/yr

The role as QuickBooks Capital credit risk lead analyst will dive into three main areas to help the ... Partner with our data science and data engineering teams to leverage the latest technology 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 ...

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

Credit Risk Data Science information

See Cupertino, CA salary details

$45.6K

$140.5K

$243.7K

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

As of Aug 26, 2026, the average yearly pay for credit risk data science in Cupertino, CA is $140,500.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,800.00 and $173,300.00 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 Cupertino, CA?

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

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

Cities near Cupertino, 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 Cupertino, 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 $140,500 per year, or $67.5 per hour.

Senior Data Scientist (Credit Risk)

Achieve

San Mateo, CA • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 14 days ago

Job description

Company Description
Achieve is a leading digital personal finance company. We help everyday people move from struggling to thriving by providing innovative, personalized financial solutions. By leveraging proprietary data and analytics, our solutions are tailored for each step of our member's financial journey to include personal loans, home equity loans, debt consolidation, financial tools and education. Every day, we get to help our members move their finances forward with care, compassion, and empathetic touch. We put people first and treat them like humans, not account numbers.
Since 2002, Achieve has grown into one of the largest private consumer fintech unicorns in the U.S., with over $40B in enrollments for our industry-leading, tech-enabled debt resolution services business, and over $11Bn in personal and home loans originations via our banking-as-a-service partner.
Job Description
We are looking for an experienced, hands-on Credit Risk, Sr. Data Scientist who is comfortable working with large data sets, coding in SQL and Python and gaining insights from the data and translating the results into actionable insights for business stakeholders. In this role, you will maintain and enhance our credit risk models/policies to monitor the portfolio and gain insights. You will also build and monitor credit risk models with an eye on loss forecasting and communicate the results to different teams such as Capital Market and Marketing. The candidate should have a passion for streamlining processes and building tools which can monitor models/portfolio effectively. You will be a key contributor to our risk management processes.
Key Responsibilities
  • Building, maintaining and enhancing credit risk models for lending portfolios.
  • Extract, clean and manipulate large data sets using SQL and Python; build pipelines and analytics to perform model and portfolio monitoring.
  • Perform exploratory data analysis (EDA) to identify portfolio trends, drivers of loss performance (vintage, credit bands, borrower attributes, macro factors) and provide insight into model deviations.
  • Maintain forecast deliverables: monthly/quarterly loss forecasts by vintage and segment, stress and scenario analyses, sensitivity testing.
  • Provide commentary and insights to business stakeholders on credit policy assumptions, model health, and emerging portfolio risks.
  • Automate reporting, dashboards and pipelines to streamline model monitoring and improve efficiency and accuracy.
  • Document model methodologies, assumptions, data sources and results in clear, audit-ready format consistent with risk governance requirements.
  • Participate in governance and review of credit model methodology, model validation support and liaise with external auditors or regulators where needed.
  • Continuously identify opportunities to improve credit decisioning accuracy, data infrastructure, modeling techniques, and integrate advanced statistical or machine-learning techniques as appropriate.

Qualifications
Required:
  • Minimum of 8 years' hands-on experience in credit risk modeling and portfolio monitoring. For example, roles in model and performance monitoring, tracking charge-offs, delinquencies, vintage analysis, roll-rates, etc.
  • Strong programming skills in Python/SQL for data analysis, modeling and automation.
  • Solid background in Probability & Statistics
  • Experience with pricing and price optimization along with analytics and monitoring related to pricing
  • Experience with credit risk modeling methodologies: Scorecard models, XGBoost, time-series analysis, vintage modeling, roll-rate curves, survival analysis or logistic regression in consumer credit risk context.
  • Familiarity with data visualization tools (e.g., Tableau, Python Widgets) or dashboarding
  • Strong analytical and critical thinking skills; ability to interpret results, identify trends, draw actionable insights and communicate clearly to non-technical stakeholders.
  • Excellent documentation skills and experience in preparing audit-ready deliverables (methodologies, assumptions, model validation support).
  • Master's degree in Economics, Statistics, Mathematics, Data Science or a related quantitative discipline (PhD preferred, but not required).

Preferred:
  • Experience in lending (personal loans or credit cards) or fintech lending environment.
  • Experience with credit risk modeling (development & monitoring)
  • Experience working with credit decisioning engines such as Oscilar, TakTile etc...
  • Experience working in CKLightbox environment
  • Experience working in the GCP environment.
  • A Passion for fintech, agile environment, ability to work both independently and in a collaborative, fast-paced team.

Additional Information
All your information will be kept confidential according to EEO guidelines.
Achieve well-being with:
  • 401 (k) with employer match
  • Medical, dental, and vision with HSA and FSA options
  • Competitive vacation and sick time off, as well as dedicated volunteer days
  • Access to wellness support through Employee Assistance Program, physical and mental health wellness programs
  • Pet care discounts for your furry family members
  • Financial support in times of hardship with our Achieve Care Fund
  • A safe place to connect and a commitment to diversity and inclusion through our six employee resource groups

Note: We will be unable to facilitate H1-B Visa transfer or sponsorship, along with STEM-OPT Visa.
Note: This role will be wokring hybrid out of our San Mateo, CA office.
Salary Range: $165,000 to $185,000 salary + bonus + benefits.
This information represents the expected salary range for this role. Should we decide to make an offer for employment, we'll consider your location, experience, and other job-related factors.
Join Achieve, change the future.
At Achieve, we're changing millions of lives.
From the single parent trying to catch up on bills to the entrepreneur needing a loan for the next phase of growth, you'll get to be a part of their journey to a better financial future. We're proud to have over 3,000 employees in mostly hybrid and 100% remote roles across the United States with hubs in Arizona, California, and Texas. We are strategically growing our teams with more remote, work-from-home opportunities every day to better serve our members. A career at Achieve is more than a job-it's a place where you can make a true impact, have a sense of belonging, establish a fulfilling career, and put your well-being first.
Attention Agencies & Search Firms: We do not accept unsolicited candidate resumes or profiles. Please do not reach out to anyone within Achieve to market your services or candidates. All inquiries should be directed to Talent Acquisition only. We reserve the right to hire any candidates sent unsolicited and will not pay any fees without a contract signed by Achieve's Talent Acquisition leader.
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