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Credit Risk Data Science Jobs in Dallas, TX (NOW HIRING)

Senior Loan Data Associate

Dallas, TX

$85K - $107K/yr

Strong understanding of loan performance metrics and credit risk concepts * Excellent written and verbal communication skills Preferred Qualifications * Master's degree in Statistics, Data Science ...

Senior Loan Data Associate

Dallas, TX · On-site

$85K - $107K/yr

Strong understanding of loan performance metrics and credit risk concepts * Excellent written and verbal communication skills Preferred Qualifications * Master's degree in Statistics, Data Science ...

Senior Loan Data Associate

Dallas, TX · On-site

$85K - $107K/yr

Strong understanding of loan performance metrics and credit risk concepts * Excellent written and verbal communication skills Preferred Qualifications * Master's degree in Statistics, Data Science ...

... data/reporting tools (e.g., Tableau)**Preferred Qualifications**- 10+ years of experience in credit risk, collections, or finance roles in B2B operations in International Corporations.- Credit Risk ...

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Credit Risk Data Science information

See Dallas, TX salary details

$36.6K

$112.7K

$195.4K

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

As of Jun 9, 2026, the average yearly pay for credit risk data science in Dallas, TX is $112,655.00, according to ZipRecruiter salary data. Most workers in this role earn between $81,600.00 and $139,000.00 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 are the key skills and qualifications needed to thrive as a Credit Risk Data Scientist, and why are they important?

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 Dallas, TX? For Credit Risk Data Science jobs in Dallas, TX, the most frequently searched job titles are:
What job categories do people searching Credit Risk Data Science jobs in Dallas, TX look for? The top searched job categories for Credit Risk Data Science jobs in Dallas, TX are:
What cities near Dallas, TX are hiring for Credit Risk Data Science jobs? Cities near Dallas, TX with the most Credit Risk Data Science job openings:
Risk Analyst II - Credit Risk Analytics

Risk Analyst II - Credit Risk Analytics

GM Financial

Fort Worth, TX • Hybrid

Full-time

Retirement

Posted 4 days ago


GM Financial rating

7.7

Company rating: 7.7 out of 10

Based on 38 frontline employees who took The Breakroom Quiz

72nd of 140 rated vehicle equipment hire


Job description

Why Credit Risk Analytics?

 GM Financial is the wholly owned captive finance subsidiary of General Motors and is headquartered in Fort Worth, U.S. We are a global provider of auto finance solutions, with operations in North America, South America and the Asia Pacific region. Through our long-standing relationships with auto dealers, we offer attractive retail financing and lease programs to meet the needs of each customer. We also offer commercial lending products to dealers to help them finance and grow their businesses. 

At GM Financial, our team members define and shape our culture - an environment that welcomes new ideas, fosters integrity and creates a sense of community and belonging. Here we do more than work - we thrive. 

Our Purpose: We pioneer the innovations that move and connect people to what matters

About the role:

Risk Analyst II - Credit Risk Analytics is responsible for analyzing credit risk exposure related to consumer and commercial loan and lease acquisition activities. The position involves conducting analysis to mitigate credit risk, create and monitor credit policy, measure credit execution and credit structure. In addition, this position will be responsible for monitoring credit performance by region, credit center, and dealership.

What makes you an ideal candidate?

  • Demonstrated understanding of data warehouses, data mining, reporting, data analysis and data visualization techniques
  • Advanced with Microsoft Excel, PowerPoint, and Word 
  • Experience with respect to data analysis and spreadsheet modeling and/or reporting 
  • Experience with coding (SAS or SQL preferred) for data mining and manipulation 
  • Querying skills and knowledge in a data warehouse environment 
  • Demonstrated quantitative skills 
  • Ability to interact collaboratively and proactively with internal customers 
  • Capable of managing multiple projects, including ability to coordinate and balance numerous tasks in a time-sensitive environment, under pressure, meeting deadlines
  • Understanding the metrics utilized in monitoring the performance of a consumer or commercial lending portfolio is a plus

Experience:

  • 2-4 years' experience working with complex Excel workbooks, querying large multi-table datasets, data analysis, and data presentation; the qualified candidate will also be able to demonstrate proficiency with the following tools: SAS and/or SQL, Microsoft Excel, PowerPoint, and Word Req 
  • 2-4 years' experience in consumer and/or commercial loan and lease origination analysis Pref 
  • Bachelor's Degree Finance, Economics, Mathematics, Business, Business Analytics, MIS, or other quantitative field; degrees in non-quantitative fields considered with adequate work experience Required 
  • Master's Degree Finance, Economics, Mathematics, Business, Business Analytics, MIS, or other quantitative field Preferred

What We Offer: Generous benefits package available on day one to include: 401K matching, bonding leave for new parents (12 weeks, 100% paid), tuition assistance, training, GM employee auto discount, community service pay and nine company holidays. 

Our Culture: Our team members define and shape our culture - an environment that welcomes innovative ideas, fosters integrity, and creates a sense of community and belonging. Here we do more than work - we thrive. 

Compensation: Competitive pay and bonus eligibility. 

Work Life Balance: Flexible hybrid work environment, 2 days a week in the office. 

In this role, you will:

  • Utilize data mining and advanced spreadsheet skills to quantify credit risk related to loan and lease origination activities
  • Summarize findings, develop recommendations and present analyses to management in a clear, concise, convincing, and actionable format 
  • Employ best practices of data analysis and validation to ensure data results are accurate 
  • Assist in the creation, maintenance and monitoring of origination credit policies, procedures and lending stipulations 
  • Understand how change to origination credit policy and lending environment can impact loan/lease volume as well as overall credit performance 
  • Proactively monitor and report relevant changes in origination trends and portfolio performance to management 
  • Conduct ad hoc research projects incorporating project design, data collection and analysis, summarization of finding, and presentation of results

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