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Credit Risk Data Science Jobs in Texas (NOW HIRING)

Master's degree in quantitative field. * 5+ years of hands-on experience in data science, credit risk analytics, or quantitative modeling. * Experience in fintech, lending, banking, or SMB credit ...

This positions will utilize advance skills to analyze data, portfolio level performance trends, custom scorecard analysis, and forecasting skills to support credit risk functions. Duties and ...

The Senior Data Scientist works with Credit, Risk, and Engineering teams to build and maintain ... of hands-on experience indata science, credit risk analytics, or quantitative modeling.

Develop and maintain machine learning models for credit risk, fraud detection, and marketing ... Master's degree (or equivalent) in Data Science, Business Analytics, or a related technical field ...

Develop and maintain machine learning models for credit risk, fraud detection, and marketing ... Master's degree (or equivalent) in Data Science, Business Analytics, or a related technical field ...

Develop and maintain machine learning models for credit risk, fraud detection, and marketing ... Master's degree (or equivalent) in Data Science, Business Analytics, or a related technical field ...

This positions will utilize advance skills to analyze data, portfolio level performance trends, custom scorecard analysis, and forecasting skills to support credit risk functions. Duties and ...

Develop and maintain machine learning models for credit risk, fraud detection, and marketing ... Master's degree (or equivalent) in Data Science, Business Analytics, or a related technical field ...

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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:
Manager, Credit Risk and Policy Analytics

Manager, Credit Risk and Policy Analytics

PenFed Credit Union

Irving, TX • Hybrid

$84K - $162K/yr

Full-time

Posted 17 days ago


PenFed Credit Union rating

7.1

Company rating: 7.1 out of 10

Based on 11 frontline employees who took The Breakroom Quiz


Job description

Overview

PenFed is hiring a (Hybrid) Manager, Credit Risk and Policy Analytics at our Tysons, Virginia or Irving, Texas location.  The primary focus of this job is to manage credit analysis to drive sustainable growth in consumer credit policy and conduct credit risk monitoring to ensure policy performance. You will explore utilizing AI in your analysis and collaborate in building advanced valuation and risk detection models. You will conduct hands-on analysis and have people management opportunities. You have a direct influence on strategic goal setting for the broader Consumer Lending Policy and Analytics team and positively impact on PenFed’s credit product experience for millions of PenFed members.


Responsibilities

Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. This is not intended to be an all-inclusive list of job duties and the position will perform other duties as assigned.

  • Develop and manage automated and judgmental decisions within credit policies for both new account acquisition and accounts on book, from approve/decline, line assignment and/or portfolio risk management.
  • Individual contributor or manage one analyst to achieve team’s strategic goals, training and assisting development of skills and cultivating credit culture.
  • Drive monitoring and analyses of credit risk for both organic and acquired portfolio, prepare related management reporting package and provide insights on root causes, emerging credit trends and implications on Allowance for Loan Losses.
  • Define risk segmentation, lead analysis for credit policy optimization and risk mitigation strategies, focusing on new account acquisition or existing account management policies.
  • Collaborate with modeling teams to build and validate risk and/or NPV valuation models using both internal and external data sources, implement models in policy optimization, and/or monitor model performance on an ongoing basis.
  • Provide ongoing or ad-hoc risk analytics to support credit or new product expansion.
  • Independently lead the effort for any ad hoc analysis and deep dive to understand the business drivers of credit trends, derive actionable insights and make sound business recommendations
  • Collaborate with business line product managers in optimizing marketing campaigns used in acquisitions and/or customer management that align with the credit policies and scoring models.
  • Participate in external and internal audits, and regulatory examinations as needed.
  • Identify required data and work with data stewards to understand data source, ensure data quality and retrieve data on a timely basis. Contribute to credit data mart and corporate database designs.
  • Explore creative ways to incorporate AI into credit analysis and BAU process.

Qualifications

Equivalent combination of education and experience is considered.

  • Bachelor’s degree in business, finance, economics, computer science, engineering, math, statistics, or other quantitative discipline required, MBA or master’s degree preferred.
  • Minimum of eight (8) years’ experience in credit risk policy & analysis, credit risk management or modeling in the financial services industry.
  • Minimum of three (3) years of supervisory / assistant manager experience required.
  • Experience in Consumer Lending products including Credit Card, Auto Loan and Unsecured Personal Loan is required.
  • Expert level skills in various data analysis and visualization tools including SQL, Excel, and PowerPoint are required.
  • Proficiency with statistical tools, R & Python and Tableau experience, is strongly preferred.
  • Excellent written, verbal communication and presentation skills.
  • Curiosity, attention to details, strong critical thinking and problem-solving skills.
  • Ability to work effectively in ambiguous situations, ability to prioritize among multiple projects.
  • Self-motivated and strong interpersonal skills to actively lead and implement ideas in a cross-functional team environment.
  • Experience using A.I. tools preferred.

Supervisory Responsibility

This position will supervise employees.

Licenses and Certifications

There are no additional licenses and/or certifications required.

Work Environment

While performing the duties of this job, the employee is regularly exposed to an indoor office setting with moderate noise.

*Most roles require working in an office setting with moderate noise and the ability to lift 25 pounds.*

Travel

Ability to travel to various worksites and be on-call is required.

Pay Transparency 
The anticipated starting salary range for this role is $84,700.00 - $162,310.00
This position is eligible for an organizational performance based annual bonus, subject to board discretion and approval.
This position is eligible for an individual performance based annual bonus.

#LI-Hybrid

Qualifications:

Equivalent combination of education and experience is considered.

  • Bachelor’s degree in business, finance, economics, computer science, engineering, math, statistics, or other quantitative discipline required, MBA or master’s degree preferred.
  • Minimum of eight (8) years’ experience in credit risk policy & analysis, credit risk management or modeling in the financial services industry.
  • Minimum of three (3) years of supervisory / assistant manager experience required.
  • Experience in Consumer Lending products including Credit Card, Auto Loan and Unsecured Personal Loan is required.
  • Expert level skills in various data analysis and visualization tools including SQL, Excel, and PowerPoint are required.
  • Proficiency with statistical tools, R & Python and Tableau experience, is strongly preferred.
  • Excellent written, verbal communication and presentation skills.
  • Curiosity, attention to details, strong critical thinking and problem-solving skills.
  • Ability to work effectively in ambiguous situations, ability to prioritize among multiple projects.
  • Self-motivated and strong interpersonal skills to actively lead and implement ideas in a cross-functional team environment.
  • Experience using A.I. tools preferred.

Supervisory Responsibility

This position will supervise employees.

Licenses and Certifications

There are no additional licenses and/or certifications required.

Work Environment

While performing the duties of this job, the employee is regularly exposed to an indoor office setting with moderate noise.

*Most roles require working in an office setting with moderate noise and the ability to lift 25 pounds.*

Travel

Ability to travel to various worksites and be on-call is required.

Pay Transparency 
The anticipated starting salary range for this role is $84,700.00 - $162,310.00
This position is eligible for an organizational performance based annual bonus, subject to board discretion and approval.
This position is eligible for an individual performance based annual bonus.

#LI-Hybrid

Education:UNAVAILABLEEmployment Type: FULL_TIME

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