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Credit Risk Modeling In Python Jobs (NOW HIRING)

In this role, you will provide insights and expertise in model development and quantitative ... Proficiency in data manipulation and analysis in a programming language such as Python or R

In this role, you will provide insights and expertise in model development and quantitative ... Proficiency in data manipulation and analysis in a programming language such as Python or R

In this role, you will provide insights and expertise in model development and quantitative ... Proficiency in data manipulation and analysis in a programming language such as Python or R

Analyzes effectiveness of credit risk models and strategies and provides insights and recommendations to leadership. Participates in projects impacting Credit Risk Management. Identifies and ...

Analyzes effectiveness of credit risk models and strategies and provides insights and recommendations to leadership. Participates in projects impacting Credit Risk Management. Identifies and ...

This role is highly analytical, with direct involvement in underwriting models and policies, line ... Proficiency in SQL and SAS; exposure to Python /Tableau or other analytical tools is a plus.

Experience with fixed income products, interest rate models, credit risk models, or mortgage models * Proficiency in Python (strongly preferred), R, MATLAB, or similar * Strong analytical and report ...

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Credit Risk Modeling In Python information

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How much do credit risk modeling in python jobs pay per hour?

As of Jun 7, 2026, the average hourly pay for credit risk modeling in python in the United States is $58.62, according to ZipRecruiter salary data. Most workers in this role earn between $48.32 and $66.59 per hour, depending on experience, location, and employer.

What is the difference between Credit Risk Modeling In Python vs Credit Risk Analyst?

AspectCredit Risk Modeling In PythonCredit Risk Analyst
Required SkillsPython programming, statistical analysis, machine learningCredit analysis, financial assessment, reporting
Work EnvironmentData science teams, quantitative departmentsBanking, lending institutions, credit departments
CertificationsData science, Python certifications, CFA (optional)CFP, CFA, credit analysis certifications
Industry UsageModel development, risk assessment, automationCredit evaluation, risk reporting, client assessment

While Credit Risk Modeling In Python focuses on developing quantitative models using programming and data analysis, Credit Risk Analyst involves evaluating individual creditworthiness and making lending decisions. Both roles require understanding of credit principles, but the modeling role emphasizes technical skills, whereas the analyst role emphasizes financial assessment and communication.

What are the key skills and qualifications needed to thrive as a Credit Risk Modeling professional in Python, and why are they important?

To excel in Credit Risk Modeling in Python, a strong background in statistics, finance, and quantitative analysis is essential, usually supported by a relevant degree in mathematics, economics, or a related field. Expertise in Python programming, familiarity with machine learning libraries (like scikit-learn or pandas), and knowledge of credit risk frameworks or regulatory standards (such as Basel III) are typically required. Analytical thinking, attention to detail, and effective communication are crucial soft skills for translating complex data into actionable insights and collaborating with stakeholders. These competencies are vital to accurately assess credit risk, meet regulatory requirements, and support sound decision-making within financial institutions.

What are some typical challenges faced by professionals working in credit risk modeling using Python?

Professionals in credit risk modeling using Python often encounter challenges related to data quality, such as missing or inconsistent information, which can impact model accuracy. Balancing regulatory compliance with innovative modeling techniques is another common hurdle, as financial institutions must adhere to strict guidelines (e.g., Basel III). Additionally, collaborating with cross-functional teams like IT, business analysts, and compliance officers is essential to ensure models are both technically robust and aligned with business objectives. Staying updated with the latest Python libraries and machine learning advancements is also important for ongoing success in this role.

What is credit risk modeling in Python?

Credit risk modeling in Python involves using statistical and machine learning techniques to predict the likelihood that a borrower will default on a loan or credit obligation. Python is widely used in this field due to its powerful data analysis libraries such as pandas, NumPy, and scikit-learn. Analysts and data scientists use these tools to build, test, and validate predictive models that assess the creditworthiness of individuals or companies. These models help financial institutions make informed lending decisions and manage their risk exposure more effectively.
What cities are hiring for Credit Risk Modeling In Python jobs? Cities with the most Credit Risk Modeling In Python job openings:
Infographic showing various Credit Risk Modeling In Python job openings in the United States as of May 2026, with employment types broken down into 94% Full Time, 3% Part Time, and 3% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $121,932 per year, or $58.6 per hour.
Credit Risk Analyst

Credit Risk Analyst

Genworth Financial, Inc.

Raleigh, NC โ€ข Hybrid

Full-time

Retirement, PTO

Posted 15 days ago


Job description

At Enact, we understand that there's no place like home. That's why we bring our deep expertise, insightful offerings, and extra mile service to work every day to help lenders put more people in homes and keep them there.

We're looking for a Credit Risk Analyst in Raleigh, NC to join us in fulfilling our mission, while utilizing our values of excellence, improvement, and connection. In this role, you will provide insights and expertise in model development and quantitative analysis of credit risk across primary and structured credit insurance opportunities. You are responsible for helping Enact succeed in its targeted acquisition, management, and distribution of credit risk strategy. Success in this role requires a blend of strong analytical skills, a desire to collaborate with others, and effective communication.

LOCATION

Enact Headquarters, Raleigh, NC - Hybrid Schedule

YOUR RESPONSIBILITIES

  • Assist in the development of new probability of default, loss given default and exposure models
  • Run developed models to assist in the quantitative assessment of both new business and portfolio performance ensuring continuity between the two
  • Review and work with external models to help validate if they are fit for use under Enact's existing Model Risk Framework
  • Incorporate internally developed and external models into Enact's data and modeling architecture
  • Monitor model performance against actual loss experience to better inform future improvements
  • Collaborate with IT teams and assist in the development of interfaces and tools that better enable underwriters to interact with model results
  • Use models and loss distributions to perform stress testing across multiple collateral types while ensuring adherence to internal and regulatory standards
  • Help in the design and computation of analytics that support Enact's capital management strategies and risk appetite.
  • Collaborate on designing strategies that inform risk acquisition and distribution

YOUR QUALIFICATIONS

  • Bachelor's degree in actuarial science, statistics, financial mathematics, or a related field
  • 3+ years of quantitative experience working with credit data and building risk models
  • Experience using statistical or machine learning to model frequency and severity of losses
  • Experience developing, testing, diagnosing and documenting risk models and their performance
  • Experience creating reproducible workflows including version-controlled code
  • Proficiency in data manipulation and analysis in a programming language such as Python or R
  • Strong communication skills that allow for collaboration across multiple teams including IT
  • Self-directed learner who proactively identifies knowledge gaps, pursues resources, and consistently applies new techniques to improve model performance or reliability

PREFERRED QUALIFICATIONS

  • Master's degree or equivalent in actuarial science, statistics, financial mathematics, or a related field
  • Experience building interactive data applications with tools such as Streamlit or Shiny
  • Experience in developing credit risk frameworks, underwriting guidance, and pricing strategies
  • Experience with cashflow modeling and financial metrics such as return on equity
  • Experience with structured credit risk transfer transactions

COMPANY
Enact Holdings, Inc. (Nasdaq: ACT), operating primarily through its wholly owned subsidiaries, is a leading publicly traded U.S. private mortgage insurance provider, offering borrower-centric products that enable lenders and other partners across the U.S. to help people responsibly achieve and maintain the dream of homeownership.

By empowering customers and their borrowers, Enact seeks to positively impact the lives of those in the communities in which it serves in a sustainable way. Headquartered in Raleigh, North Carolina, we play an active role in supporting a healthier Triangle community. We also support our colleagues' philanthropic efforts in their home communities across the U.S. Enact values all perspectives, characteristics and experiences, along with providing a positive and inclusive culture for employees to grow and succeed. We strive to create an environment where employees can bring their full, authentic selves to work to help each other and their customers.

We are proud to be an equal opportunity employer and all hiring decisions are based on merit, qualifications, and business needs. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.

WHY WORK AT ENACT

  • We bring innovative thinking to the situations at hand
  • We seek out and incorporate diverse views to strengthen our outcomes
  • We work on challenging and rewarding projects
  • We offer competitive benefits:
    • Hybrid work schedule (in-office days Tues/Wed/Thurs)
    • Generous Time Off
    • 40 Hours of Volunteer Time Off
    • Tuition Reimbursement and Student Loan Repayment
    • Paid Family Leave and Flexible Spending Accounts
    • 401k with up to 5% employer match
    • Fitness and Emotional Wellness Reimbursements
    • Onsite Gym