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Freelance Credit Risk Modeling Jobs in Virginia (NOW HIRING)

Produce financial models and NPV analyses About You (Qualifications) * Bachelor's degree in a ... credit risk * 1+ years at a fast-moving start-up * Experience using in data science and machine ...

Produce financial models and NPV analyses About You (Qualifications) * Bachelor's degree in a ... credit risk * 1+ years at a fast-moving start-up * Experience using in data science and machine ...

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Freelance Credit Risk Modeling information

What is freelance credit risk modeling?

Freelance credit risk modeling involves independent professionals analyzing and predicting the likelihood that borrowers or counterparties will default on financial obligations. These freelancers use statistical methods, machine learning models, and data analysis to assess credit risk for banks, lenders, or other firms. Their work helps organizations make informed lending decisions, set appropriate interest rates, and comply with regulatory requirements. Freelancers in this field may work on projects like developing credit scorecards, stress testing portfolios, or validating existing risk models.

How do freelance credit risk modelers typically collaborate with clients and other stakeholders during projects?

Freelance credit risk modelers usually work closely with client teams such as credit analysts, data engineers, and compliance officers to understand data sources, project objectives, and regulatory requirements. Communication often occurs through regular virtual meetings, progress reports, and collaborative tools to ensure transparency and alignment. Freelancers must be proactive in clarifying goals, sharing preliminary findings, and incorporating feedback to deliver models that meet both technical and business needs. Building strong client relationships and maintaining clear documentation are key to successful collaboration in this role.

What are the key skills and qualifications needed to thrive as a freelance credit risk modeler, and why are they important?

To thrive as a Freelance Credit Risk Modeler, you need a strong background in statistics, quantitative finance, and data analysis, typically supported by a degree in finance, mathematics, or a related field. Proficiency in programming languages such as Python, R, or SAS, along with experience using risk modeling software and knowledge of regulatory frameworks like Basel III, is crucial. Excellent communication, project management, and client relationship skills help distinguish top freelancers in this role. These abilities are essential for delivering accurate risk assessments, meeting client expectations, and maintaining compliance in a dynamic financial environment.

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

AspectFreelance Credit Risk ModelingCredit Analyst
CredentialsRelevant certifications (e.g., CFA, credit risk certifications), strong quantitative skillsTypically requires a degree in finance, economics, or related field; certifications are a plus
Work EnvironmentIndependent, project-based, remote or client-siteUsually in banks, financial institutions, or corporate offices
Industry UsageUsed by consulting firms, freelance platforms, and financial servicesEmployed directly by financial institutions or corporations
Comparison Search IntentUnderstanding freelance opportunities in credit risk modelingAssessing creditworthiness and risk for lending decisions

Freelance Credit Risk Modeling involves independent, project-based work focusing on developing risk models, often remotely. Credit Analysts work within organizations to evaluate creditworthiness, typically in a structured environment. While both roles require financial expertise and similar credentials, their work settings and employment types differ significantly.

What are popular job titles related to Freelance Credit Risk Modeling jobs in Virginia?

For Freelance Credit Risk Modeling jobs in Virginia, the most frequently searched job titles are:

What job categories do people searching Freelance Credit Risk Modeling jobs in Virginia look for?

The top searched job categories for Freelance Credit Risk Modeling jobs in Virginia are:

Infographic showing various Freelance Credit Risk Modeling job openings in Virginia as of September 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, 3% Contract, and 1% Nights. Highlights an 82% Physical, 5% Hybrid, and 13% Remote job distribution.

Senior Data Scientist, Credit Risk & ML Platforms

Mclean, VA • On-site

Information Technology Senior Management Forum
11 - 50 employees

Other

Posted 23 days ago


Job description

Senior Associate, Data Scientist - Consumer Credit Risk Models and Data

Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making.

As a Data Scientist at Capital One, you’ll be part of a team that’s leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.

Team Description

Have you ever seen the headline in the news “Banks Pass Federal Reserve Stress Tests” and wondered how Capital One determines how much savings (or “capital”) it needs? Or maybe how we analyze the potential impact of the next recession? At the heart of these questions are sophisticated econometric loss models that help us understand the ways in which the economy impacts our loan portfolios and guide strategic decision making at the highest levels of Capital One.

In the Consumer Credit Risk Management Models and Data Team, we blend cutting-edge quantitative methods, with a deep understanding of our business, data, and regulatory environment to build and deploy predictive models for losses, account volumes and outstanding balances. These models drive key strategic decisions for loss allowances, stress testing, and capital allocation as well as informing our earnings calls and recession preparedness.

If this sounds interesting to you, join us! As a Data Scientist on the deployment & platform side of the team, you’ll be at the forefront helping us to usher in the next wave of disruption by using the latest technology to deploy, optimize and modernize model pipelines and execution platforms that enable machine learning models to provide powerful insights about our portfolio and growth opportunities through new data sources. You will partner with best-in-class data scientists, analysts, and engineers to innovate solutions that directly impact the company’s bottom line in a meaningful way. You will do it all in a collaborative environment that values your insight, encourages you to take on new responsibilities, promotes continuous learning, and rewards innovation.

Role Description In this role, you will:
  • Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love
  • Leverage a broad stack of technologies — Python, Conda, AWS, H2O, Spark, and more — to reveal the insights hidden within huge volumes of numeric and textual data
  • Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation
  • Flex your interpersonal skills to translate the complexity of your work into tangible business goals
The Ideal Candidate is:
  • Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them.
  • Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You’re not afraid to share a new idea.
  • Technical. You’re comfortable with open-source languages and are passionate about developing further. You have hands‑on experience developing data science solutions using open‑source tools and cloud computing platforms.
  • Statistically‑minded. You’ve built models, validated them, and backtested them. You know how to interpret a confusion matrix or a ROC curve. You have experience with clustering, classification, sentiment analysis, time series, and deep learning.
  • A data guru. “Big data” doesn’t faze you. You have the skills to retrieve, combine, and analyze data from a variety of sources and structures. You know understanding the data is often the key to great data science.
Basic Qualifications:
  • Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date:
    • A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 2 years of experience performing data analytics
    • A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration
Preferred Qualifications:
  • Master’s Degree in “STEM” field (Science, Technology, Engineering, or Mathematics), or PhD in “STEM” field (Science, Technology, Engineering, or Mathematics)
  • Experience working with AWS
  • At least 2 years’ experience in Python, Scala, or R
  • At least 2 years’ experience with machine learning
  • At least 2 years’ experience with SQL

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

McLean, VA: $135,600 - $154,800 for Sr Assoc, Data Science

Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.

This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.

Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.

This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug‑free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.

If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com.

Capital One does not provide, endorse nor guarantee and is not liable for third‑party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

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