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

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 ...

Us Bank

Credit Risk Analyst

San Francisco, CA · On-site

$93 - $109/hr

The organization's risk management structure is designed to promote effective governance and risk ... This role will perform data analyses and share results, using such tools as SAS, SQL, Toad, Python ...

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 ...

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 ...

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Credit Risk Data Science information

See Concord, CA salary details

$40.6K

$125K

$216.7K

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

As of Sep 4, 2026, the average yearly pay for credit risk data science in Concord, CA is $124,958.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,500.00 and $154,200.00 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 job categories do people searching Credit Risk Data Science jobs in Concord, CA look for?

The top searched job categories for Credit Risk Data Science jobs in Concord, CA are:

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

Cities near Concord, 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 Concord, CA as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 15% Part Time, and 3% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $124,958 per year, or $60.1 per hour.

Credit Strategy Manager

SoFi

San Francisco, CA • On-site

Full-time

Re-posted 26 days ago

Job description

SoFi's Credit team manages credit risk activities for our lending products (Student Loan Refinance, Private Student Loan, Personal Loan, Credit Card, and Mortgage) - including credit strategies/policies for new account origination and portfolio management, collections/recovery strategies and operations, and risk and operational data science and analytics. The team designs data-driven strategies to ensure the growth in lending is consistent with the company's risk appetite and helps create the products and experiences that put our members' interests first.

The Credit Strategy Lead will work in the Credit team and have responsibilities to analyze and evaluate data to develop and propose value-added credit risk strategies and models for SoFi's lending products, including Personal Loan, Student Loan Refinance, Private Student Loan, and Credit Card.

The Credit Strategy Lead will collaborate with cross-functional teams such as Business Units, Capital Markets, Product and Engineering, and use business knowledge and quantitative and analytical skills to drive revenue, control risk, and provide value to the company and consumers.

The ideal candidate will possess a data-driven analytics background and the strategic acumen to direct a function that draws strategic insights from data using database and statistical analysis tools to inform decisions and support SoFi's overarching strategic goals relative to loss prevention and profit optimization. They bring new ways of thinking, data sources, technologies, and capabilities to SoFi.

What you'll do:

  • Innovate... Bring your brightest ideas to building risk strategies. This means you will architect the pre-screen and underwriting strategies.
  • Data Driven... Your deep analysis will power the future of lending with an optimal real-time data ecosystem - including multi-product internal, bureau, third-party, and alternative data sources and uses.
  • Iterate, learn, innovate... We are all responsible for innovation and must embrace data-driven decisions.
  • Control the Risk and Drive Performance Outcomes ... Understand credit risk and develop approaches to mitigate loss and responsibly grow revenue. Monitor the performance of strategies and portfolios. Document and communicate results and escalate issues as necessary. Identify gaps/opportunities and drive actions.
  • Grow, Grow, Grow!... Be inspired by dynamic leaders and our rapidly growing business. We want YOU to be an inspired leader of tomorrow, so we are recruiting the best, brightest, and passionately quantitative team members.

What you'll need:

  • 4+ years of related experience
  • Business acumen and work experience in the consumer lending business (loans or credit cards)
  • Direct experience in the credit strategy analytical life cycle, including strategy and decision tree development, presentation, implementation validation, and post-implementation monitoring
  • Proven analytical skills in conducting sophisticated analysis using customer performance data, bureau attributes, and other 3rd party variables to solve business problems
  • Proficient skills in Excel, SQL and Python
  • A demonstrated ability to synthesize and communicate analysis to business partners and senior management
  • High motivation to drive results, eager to learn, and able to work collaboratively in a fluid environment
  • Knowledge/skills in analytical and modeling techniques such as Decision Trees, regression, logistic regression, A/B Testing, and Tableau
  • Preferred: 4+ years of consumer lending credit strategy work experience
  • Preferred: Experience in analyzing and testing credit strategies or models to meet the fair lending requirements
  • Preferred: Advanced degree (Master's or PhD) with a quantitative major such as Statistics, Mathematics, Engineering, or Computer Science

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