1

Credit Risk Data Science Jobs in Washington (NOW HIRING)

Senior Credit Risk Manager

Washington, DC ยท On-site

$100K - $140K/yr

Ensure accuracy, integrity, and consistency of risk data and reporting Collateral, Margining ... in credit risk, counterparty risk, or financial risk management * Strong experience within ...

Senior Credit Risk Manager

Washington, DC ยท On-site

$100K - $140K/yr

Ensure accuracy, integrity, and consistency of risk data and reporting Collateral, Margining ... in credit risk, counterparty risk, or financial risk management * Strong experience within ...

IFC's Credit and Investment Risk Department (CIR) is looking to fill a Risk Officer (F2) position ... Develop databases and data extraction and reporting of risk rating data in combination with data ...

... data-driven, and compliant with evolving regulatory expectations. The Manager will partner closely with First Line business teams while maintaining independence, contribute to executive and committee ...

The Credit Manager for Single-Family Seller Credit Risk Management is tasked with identifying ... Analytical and data-driven approach to risk assessment, along with interest in utilizing AI tools ...

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

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.

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 popular job titles related to Credit Risk Data Science jobs in Washington? For Credit Risk Data Science jobs in Washington, the most frequently searched job titles are:
What job categories do people searching Credit Risk Data Science jobs in Washington look for? The top searched job categories for Credit Risk Data Science jobs in Washington are:
What cities in Washington are hiring for Credit Risk Data Science jobs? Cities in Washington with the most Credit Risk Data Science job openings:
Infographic showing various Credit Risk Data Science job openings in Washington as of May 2026, with employment types broken down into 91% Full Time, 8% Part Time, and 1% Contract. Highlights an 74% Physical, 3% Hybrid, and 23% Remote job distribution.

Data Scientist - Private Equity, Private Credit Risk, & Performance Analysis

GXM Technologies LLC

Washington, DC โ€ข On-site

Full-time

Posted 13 days ago


Job description

Description:

GXM is seeking a highly motivated and analytically rigorous Data Scientist with deep experience in Private Equity and Private Credit risk and performance analysis to support a high-priority federal investment program focused on accelerating the development and deployment of emerging technologies critical to national and economic security.


This role combines advanced quantitative analysis, alternative investment evaluation, and risk modelling to support senior government stakeholders in making informed capital allocation decisions and to report on program performance. The selected candidate will work at the intersection of finance, data science, and national strategic priorities, analyzing complex investment structures, portfolio performance, and risk indicators across a broad range of innovative technology sectors.


The ideal candidate brings strong expertise in private markets investing, financial modeling, performance and risk analytics, and data-driven decision support, along with the ability to operate effectively in a fast-paced, high-visibility federal environment. This individual will also mentor junior analysts, contribute to cross-functional collaboration, and help improve investment evaluation systems and analytical workflows.


This position is based in the Washington, DC metropolitan area and requires on-site presence five days per week.


Key Responsibilities

  • Lead advanced quantitative analysis of private equity funds, private credit portfolios, portfolio companies, and alternative investment structures.
  • Perform risk and performance analysis across investment portfolios, including credit risk, valuation trends, liquidity exposure, portfolio concentration, and capital deployment effectiveness.
  • Develop and maintain analytical models to assess investment opportunities, portfolio health, and long-term strategic outcomes.
  • Evaluate emerging technology sectors and companies for alignment with federal investment priorities, including dual-use, commercial, and defense-related applications.
  • Produce investment memorandums, executive briefings, dashboards, and data visualizations for senior government leadership and stakeholders.
  • Apply advanced data science, statistical modeling, machine learning, and predictive analytics techniques to large structured and unstructured datasets.
  • Develop automated workflows and scalable analytical processes to support investment analysis and reporting functions.
  • Contribute to the development and refinement of investment policies, reporting frameworks, governance processes, and risk mitigation strategies.
  • Identify trends and risks indicators across investment and technology datasets to support strategic decision-making.
Requirements:
  • U.S. Citizen required and will be verified in-person; no clearance required.
  • Bachelorโ€™s or Masterโ€™s degree in Data Science, Finance, Economics, Statistics, Business Analytics, or a related quantitative field.
  • 5โ€“7 years of experience in private equity, private credit, investment analytics, quantitative finance, or related financial analytical roles.
  • Experience performing private equity and private credit risk and performance analysis, including portfolio analytics, valuation assessment, and investment risk evaluation.
  • Experience developing dashboards and visualizations using Power BI, Tableau, or similar tools.
  • Strong analytical, statistical, and financial modeling skills with the ability to communicate findings to executive stakeholders.
  • Experience working in fast-paced, high-visibility environments with cross-functional teams and senior leadership.

Desired Qualifications

  • Experience supporting federal investment, innovation, economic development, or technology modernization initiatives.
  • Knowledge of emerging technology sectors such as artificial intelligence, advanced manufacturing, semiconductors, energy, autonomy, cybersecurity, biotechnology, or defense technologies.
  • Familiarity with federal investment governance, public-private partnerships, or interagency coordination environments.
  • Experience applying machine learning or AI techniques to financial forecasting, investment screening, or risk analysis.
  • Understanding of technology commercialization and transition challenges, including operational adoption and scaling constraints.

Equal Employment Opportunity / Legal Disclaimer

GXM Technologies LLC is an Equal Opportunity Employer and participates in E-Verify to confirm employment eligibility. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy), sexual orientation, gender identity, national origin, age, disability, genetic information, veteran status, or any other legally protected status. GXM Technologies LLC provides reasonable accommodations in accordance with applicable law. This job description is not intended to be a complete list of duties and responsibilities, which may change at any time with or without notice. Employment is at-will where permitted by law, meaning either the employee or the Company may terminate employment at any time, with or without cause or notice, subject to applicable legal requirements.?