1

Credit Risk Data Science Jobs in Texas (NOW HIRING)

Strong experience with Python for data analysis and modeling * Working knowledge of credit risk concepts: scorecards, vintage analysis, delinquency curves, loss forecasting * Ability to communicate ...

New

Senior Data Scientist Function: Credit Risk Reports to: Head of Credit Level: Mid-Level / Senior Location: Addison, TX (5 days/week in-office) Please note: This position is open to candidates within ...

Senior Data Scientist Function: Credit Risk Reports to: Head of Credit Level: Mid-Level / Senior Location: Addison, TX (5 days/week in-office) Please note: This position is open to candidates within ...

You will be instrumental in complex data gathering and sophisticated analysis, contributing ... scientific, engineering, business or technical field; OR an equivalent level of demonstrated ...

Credit Risk Analytics Manager I

Plano, TX · On-site +1

$103K - $197K/yr

You will be instrumental in complex data gathering and sophisticated analysis, contributing ... scientific, engineering, business or technical field; OR an equivalent level of demonstrated ...

Credit Risk Analytics Manager I

Plano, TX · On-site +1

$103K - $197K/yr

You will be instrumental in complex data gathering and sophisticated analysis, contributing ... scientific, engineering, business or technical field; OR an equivalent level of demonstrated ...

You manipulate large amounts of data, extract key insights from the data, and then clearly and ... credit risk management or comparable process management experience * Graduate degree in a ...

Credit Risk Analytics Manager I

Plano, TX · On-site

$103K - $197K/yr

You will be instrumental in complex data gathering and sophisticated analysis, contributing ... scientific, engineering, business or technical field; OR an equivalent level of demonstrated ...

Environmental Credit Risk Associate Bring your expertise to JPMorganChase. As part of Risk ... Bachelor's degree or equivalent education in environmental sciences or related fields, and may hold ...

You will be instrumental in complex data gathering and sophisticated analysis, contributing ... scientific, engineering, business or technical field; OR an equivalent level of demonstrated ...

... data science experience in financial services or the mortgage industry; experience in online lending is a plus. • Comprehensive knowledge of the mortgage lifecycle, including credit risk ...

This role requires deep expertise in credit risk frameworks, and data analytics, with a strong ... Partner closely with data science teams to deploy and interpret predictive models, model forecasts ...

next page

Showing results 1-20

Credit Risk Data Science information

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

Senior Credit Risk Analyst

Braviant Holdings

Dallas, TX • Hybrid

Full-time

Posted 2 days ago

New


Job description

Title: Senior Credit Risk Analyst
Function: Credit Risk
Reports to: Head of Credit
Level: Mid-Level / Senior
Location: Addison, TX (5 days/week in-office)

Please note: This position is open to candidates within commuting distance to the DFW metro area only. Applicants must reside in Texas and be authorized to work in the United States. Applications from candidates outside of Texas will not be considered at this time. While we appreciate interest from all applicants, Braviant Holdings is unable to sponsor visas at this time.

Who We Are

Founded in 2015 and based in Chicago, IL, privately held Braviant Holdings, LLC is a leading provider of tech-enabled consumer credit products that combine breakthrough technology and cutting-edge machine learning to transform how people access credit online. Our next-generation approach to lending reduces credit barriers and creates a Path to Prime®, helping millions of underbanked consumers build credit history, reduce their cost of borrowing, and take control of their personal finances. Braviant has been named multiple times to the Inc. 5000 list of fastest growing private companies and has been recognized as a Best Place to Work.

We are a lean team of approximately 40 people. Everyone rolls up their sleeves here, including this role.

Position Summary

The Senior Credit Risk Analyst supports the full credit risk lifecycle at Braviant, from originations strategy and underwriting analytics to portfolio monitoring and loss forecasting. This is a highly technical, execution-focused role for someone who is equally comfortable writing production SQL/Python, building a segmentation strategy, and presenting findings to senior leadership. You will work directly with the Head of Credit to develop and refine the risk strategies that drive portfolio performance across our direct mail and digital lending channels.

This is a hands-on, high-impact role suited for someone who is analytical, detail-oriented, and biased toward action, not just case review. 

What You'll Be Doing
  • Track and analyze key portfolio metrics including FPD, GNS, delinquency roll rates, and D2M performance across origination cohorts and risk segments
  • Build and maintain dashboards and recurring reporting that surface early warning signals and portfolio trends
  • Conduct vintage analysis, loss curve development, and cohort-level performance reviews to support monthly and quarterly business reviews
  • Support the design and evaluation of originations strategies, score cutoffs, and underwriting policy changes across DM and digital channels
  • Analyze the performance impact of ongoing A/B tests and pricing experiments, translating results into actionable recommendations
What You Will Bring
Required
  • 3 to 5 years of experience in credit risk, consumer lending analytics, or a closely related quantitative role
  • Strong SQL skills; you write complex queries without a template
  • Strong experience with Python for data analysis and modeling
  • Working knowledge of credit risk concepts: scorecards, vintage analysis, delinquency curves, loss forecasting
  • Ability to communicate analytical findings clearly to non-technical stakeholders
 
Preferred
  • Experience in subprime consumer lending, fintech, payments, or another regulated financial services technology environment.
  • Familiarity with credit decisioning, underwriting strategy, or fraud detection
  • Experience working in a regulated financial services environment
  • Exposure to A/B testing, experimentation frameworks, or champion/challenger strategies
Benefits & Perks

Compensation at Braviant is competitive and commensurate with experience. Details will be discussed with qualified candidates during the interview process. In addition, we provide:

  • Comprehensive healthcare including medical, dental, and vision coverage
  • Generous paid time off, including PTO, sick time, and 13 company holidays
  • 401(k) with company contribution
  • Participation in annual discretionary bonus plan
  • Regular team and company gatherings
Braviant is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity or expression, age, marital status, veteran status, disability status, or any other characteristic protected by applicable law.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.