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Credit Risk Data Science Jobs in Washington, DC (NOW HIRING)

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Credit Risk Data Science information

See Washington, DC salary details

$41.9K

$129K

$223.7K

How much do credit risk data science jobs pay per year?

As of Jul 7, 2026, the average yearly pay for credit risk data science in Washington, DC is $128,981.00, according to ZipRecruiter salary data. Most workers in this role earn between $93,400.00 and $159,100.00 per year, depending on experience, location, and employer.

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 job categories do people searching Credit Risk Data Science jobs in Washington, DC look for? The top searched job categories for Credit Risk Data Science jobs in Washington, DC are:

Head of Data Science -- Credit Risk & Fraud Analytics (Rockville)

Gravity Engineering Services Pvt Ltd.

Rockville, MD โ€ข On-site

Full-time

Posted 3 days ago


Job description

Gravity Engineering Services Pvt Ltd. is seeking a Head of Data Science for OpenSky who will lead strategy and execution of analytics solutions for our credit card lending business. This hands-on leadership role offers a unique opportunity to build credit risk models from scratch and influence business growth through advanced analytics.

The ideal candidate will have over 10 years of data science experience, with a strong record in financial services, and proven leadership abilities in building teams. Proficiency in SQL and Python is essential.

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