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Hourly Credit Risk Modeling Jobs in Virginia (NOW HIRING)

... risk management. * In collaboration with the Senior Credit Officer, helps model, project and track ... actual versus potential charge-offs, NPL's, criticized and classified assets and overall credit ...

Region Credit Controller

Chesapeake, VA · Hybrid

$100K - $111K/yr

Performing financial modeling, quantitative risk analysis, and advanced regulatory complianc * Working with U.S. and international credit regulations, ensuring full compliance with financial ...

Region Credit Controller

Chesapeake, VA · On-site

$100K - $111K/yr

Performing financial modeling, quantitative risk analysis, and advanced regulatory complianc * Working with U.S. and international credit regulations, ensuring full compliance with financial ...

... risk management. * In collaboration with the Senior Credit Officer, helps model, project and track ... actual versus potential charge-offs, NPL's, criticized and classified assets and overall credit ...

Quantitative Analytics Senior

Mclean, VA · On-site

$126K - $190K/yr

Developing analytical methods and models that assess the credit risk of new and existing financial and mortgage products * Providing resolutions to an extensive range of complicated problems ...

SUMMARY Analyzes credit worthiness and credit risk of commercial borrowers, including review of ... Serves as a model of excellent customer service to other employees. * Identifies and cross-sells ...

SUMMARY Analyzes credit worthiness and credit risk of commercial borrowers, including review of ... Serves as a model of excellent customer service to other employees. * Identifies and cross-sells ...

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Hourly Credit Risk Modeling information

What is hourly credit risk modeling?

Hourly credit risk modeling is the process of assessing and predicting the likelihood of a borrower defaulting on their financial obligations, with risk evaluated and updated on an hourly basis. This approach is often used by financial institutions and fintech companies that require real-time credit risk analysis for instant lending decisions or ongoing portfolio monitoring. By utilizing real-time data and advanced analytics, hourly credit risk modeling enables lenders to respond quickly to changes in a borrower's financial behavior or external market conditions. This leads to more accurate risk assessments and helps institutions manage their exposure more effectively.

What is the difference between Hourly Credit Risk Modeling vs Credit Analyst?

AspectHourly Credit Risk ModelingCredit Analyst
Primary FocusDeveloping and implementing credit risk models to assess borrower riskAnalyzing credit data to evaluate creditworthiness of individuals or companies
Required SkillsStatistical analysis, modeling, programming, financial analysisFinancial analysis, credit report review, communication skills
Work EnvironmentFinancial institutions, consulting firms, often project-basedBanks, lending institutions, credit departments
CertificationsOften requires CFA, FRM, or similar certificationsTypically requires finance or accounting degrees; certifications like CFA are common

Hourly Credit Risk Modeling involves creating quantitative models to predict credit risk, often requiring advanced statistical and programming skills. Credit Analysts focus on evaluating individual credit data to make lending decisions. While both roles require financial knowledge and may share certifications, their core responsibilities differ: one is model development, the other is credit evaluation.

What are the key skills and qualifications needed to thrive as an Hourly Credit Risk Modeler, and why are they important?

To thrive as an Hourly Credit Risk Modeler, you need strong quantitative skills, a background in finance, economics, mathematics, or statistics, and experience with credit risk principles. Familiarity with statistical software such as SAS, R, or Python, as well as knowledge of risk modeling frameworks and regulatory requirements, is typically required. Analytical thinking, attention to detail, and effective communication are crucial soft skills for interpreting data and presenting findings to stakeholders. These skills are essential for accurately assessing credit risk, supporting sound decision-making, and ensuring regulatory compliance in financial institutions.

How does an Hourly Credit Risk Modeling professional typically collaborate with other departments within a financial institution?

Hourly Credit Risk Modeling professionals often work closely with teams such as underwriting, data analytics, and IT to ensure credit risk models are accurate and actionable. They may participate in cross-functional meetings to discuss model performance, share insights from data analysis, and implement feedback from business stakeholders. Collaboration is key, as their models directly influence lending decisions, risk management strategies, and regulatory compliance. Regular communication with colleagues helps ensure that risk models stay aligned with evolving business needs and regulatory requirements.
What are the most commonly searched types of Credit Risk Modeling jobs in Virginia? The most popular types of Credit Risk Modeling jobs in Virginia are:
What are popular job titles related to Hourly Credit Risk Modeling jobs in Virginia? For Hourly Credit Risk Modeling jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Hourly Credit Risk Modeling jobs in Virginia look for? The top searched job categories for Hourly Credit Risk Modeling jobs in Virginia are:
What cities in Virginia are hiring for Hourly Credit Risk Modeling jobs? Cities in Virginia with the most Hourly Credit Risk Modeling job openings:
Sr Data Scientist, NPV Modeling

Sr Data Scientist, NPV Modeling

PenFed Credit Union

Mclean, VA • Hybrid

Full-time

Posted 12 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) Sr Data Scientist, NPV Modeling at our Tysons, Virginia location. The primary purpose of this job is to develop, maintain and enhance Auto, Personal Loan and Credit Card NPV calculator used to support credit decisioning, pricing, engagement and other business strategies. In addition, this role supports the first line's independent challenge of official loss forecast for consumer lending portfolios.


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.

  • Lead interaction with and advising Management of regarding credit risk issues; formulates product strategy recommendations and evaluates the risk in the overall loan portfolio.

  • Conduct autonomous end-to-end more complex statistical model creation, including but not limited to identifying objectives, compiling data, sampling/prepping data, feature selection, model comparison/selection, deployment, and monitoring.

  • Ensures adequate internal control processes around model development, implementation and validation are established.

  • Develop, monitor, and maintain risk models using advanced machine learning and statistical method.

  • Research and recommend new approaches/algorithms to identify relationships among complex data and implements model changes to improve model performance.

  • Understand the trends within consumer and commercial loans portfolio, their impact on model implementation design and performance, and develop timely approach to address changes.

  • Develop necessary analytics and processes during model implementation and forecasting process to provide production support and resolution.

  • Establish consistent and robust model implementation processes across models with effective review and controls.

  • Communicate design and results of model’s development and implementation to a variety of audiences, including senior management, bank supervisors, internal validation, Internal Audit and line of business credit and finance end users.

  • Apply intermediate to advanced knowledge of financial processes and procedures, and routine modeling theories and techniques to create effective modeling solutions for a single or multiple business functions.

  • Maintain documentation for key processes and model components across the team with focus on standardization of processes.

  • Engage model development teams, model production, and forecasting/model production team/users to develop consistent model implementation and process capabilities.

  • Participate in regular interactions with various stakeholders to enhance model implementation processes and translate requirements into integrated forecasting process/tools for effective consumption.

  • Translate requirements into integrated forecasting process/tools for effective consumption.


Qualifications

Equivalent combination of education and experience is considered.

  • Master’s Degree in quantitative discipline is required.  PHD is highly preferred.

  • Minimum of three (3) years of related work experience in building statistical models and advanced data analysis. Minimum of one (1) years of experience for PhD degree holders.

  • Applied experience with Logistic Regression, Linear Regression, Machine Leaning, and Survival Analysis required.

  • Advanced programming skills to include knowledge of statistical programs (e.g. SQL, Python, and R) required.

  • Ability to manage multiple projects simultaneously and implement rapid changes in project direction.

  • Demonstrate strong data analysis skills, ability to understand underlying data and complex loss/balance forecasting models, various product features, possess organizational and prioritization skills, as well as strong attention to detail.

  • Detail oriented, results driven, and the ability to navigate in a quickly changing and high demand environment to develop solutions while balancing multiple priorities.

  • Critical thinking using both analytical and tactical approach to problem solving within the Quantitative Modeling team is required.

  • Ability to interact effectively with team members across the management team, Lines of Business (LOB), credit officers, finance, model governance, oversight, validation, and audit organizations.

  • Proven project management skills.

  • Excellent oral and written communication skills required.

  • Experience using A.I. tools preferred

Supervisory Responsibility

This position will not supervise employees.

Licenses and Certifications

There are no additional 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 not required.

#LI-Hybrid

Qualifications:

Equivalent combination of education and experience is considered.

  • Master’s Degree in quantitative discipline is required.  PHD is highly preferred.

  • Minimum of three (3) years of related work experience in building statistical models and advanced data analysis. Minimum of one (1) years of experience for PhD degree holders.

  • Applied experience with Logistic Regression, Linear Regression, Machine Leaning, and Survival Analysis required.

  • Advanced programming skills to include knowledge of statistical programs (e.g. SQL, Python, and R) required.

  • Ability to manage multiple projects simultaneously and implement rapid changes in project direction.

  • Demonstrate strong data analysis skills, ability to understand underlying data and complex loss/balance forecasting models, various product features, possess organizational and prioritization skills, as well as strong attention to detail.

  • Detail oriented, results driven, and the ability to navigate in a quickly changing and high demand environment to develop solutions while balancing multiple priorities.

  • Critical thinking using both analytical and tactical approach to problem solving within the Quantitative Modeling team is required.

  • Ability to interact effectively with team members across the management team, Lines of Business (LOB), credit officers, finance, model governance, oversight, validation, and audit organizations.

  • Proven project management skills.

  • Excellent oral and written communication skills required.

  • Experience using A.I. tools preferred

Supervisory Responsibility

This position will not supervise employees.

Licenses and Certifications

There are no additional 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 not required.

#LI-Hybrid

Education:UNAVAILABLEEmployment Type: FULL_TIME

What PenFed Credit Union employees say

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