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Credit Risk Data Science Jobs in Philadelphia, PA

Continental Finance

Credit Risk Analyst

Wilmington, DE · Hybrid

We are seeking a Data Analyst to support our Credit Risk team. Seeking a Data Analyst to support direct mail and Invitation-To-Apply (ITA) acquisition campaigns through targeting, list processing and ...

Td

Credit Risk Strategy Manager I (US)

Wilmington, DE · On-site

$120K - $145K/yr

Experience in data modeling and risk management either from a business administration, statistical ... scientific or financial background * Excellent written and verbal communication skills

Td

Risk Manager I (US)

Wilmington, DE · On-site

$91K - $136K/yr

The position is expected work with data vendors such as Credit bureaus to obtain and validate ... scientific or financial background * Excellent written and verbal communication skills

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All JobsCredit Risk Data Science JobsCredit Risk Data Science Jobs in Philadelphia, PA

Credit Risk Data Science information

See Philadelphia, PA salary details

$37.3K

$114.9K

$199.3K

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

As of Aug 9, 2026, the average yearly pay for credit risk data science in Philadelphia, PA is $114,916.00, according to ZipRecruiter salary data. Most workers in this role earn between $83,200.00 and $141,800.00 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 skills and qualifications are needed to thrive as a credit risk data scientist?

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 are popular job titles related to Credit Risk Data Science jobs in Philadelphia, PA? For Credit Risk Data Science jobs in Philadelphia, PA, the most frequently searched job titles are:
What job categories do people searching Credit Risk Data Science jobs in Philadelphia, PA look for? The top searched job categories for Credit Risk Data Science jobs in Philadelphia, PA are:
What cities near Philadelphia, PA are hiring for Credit Risk Data Science jobs? Cities near Philadelphia, PA with the most Credit Risk Data Science job openings:
Credit Risk Data Science jobs near you
Infographic showing various Credit Risk Data Science job openings in Philadelphia, PA as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $114,916 per year, or $55.2 per hour.

Credit Risk Analyst

Continental Finance Company

Wilmington, DE • On-site

Full-time

Re-posted 8 days ago

Job description

Come join a growing financial technology company that’s leading the marketplace in both the marketing and servicing of credit cards! Continental Finance Company specializes in credit card options for those consumers with less than perfect credit. We are seeking a Data Analyst to support our Credit Risk team.

Seeking a Data Analyst to support direct mail and Invitation-To-Apply (ITA) acquisition campaigns through targeting, list processing and execution, and credit risk performance analysis, helping drive efficient growth while maintaining strong portfolio performance.

Essential Functions:

  • Execute end-to-end direct mail and ITA campaigns, including selection of prospective customers, list processing, and file delivery.
  • Perform credit risk analysis to support targeting, offer strategy, and campaign decisioning.
  • Monitor campaign performance, including response, approval, and early credit indicators.
  • Identify, analyze, and report production trends to management.
  • Partner with Marketing, Operations, IT to ensure accurate and timely campaign execution.
  • Leverage credit bureau data, models, and new data sources to enhance targeting and credit risk strategies.
  • Support test-and-learn initiatives and deliver actionable insights to optimize campaign performance.
  • Maintain documentation and ensure data accuracy, controls, and compliance with internal policies.

The ideal candidate will have the following:

  • Bachelor’s degree in quantitative fields such as Mathematics, Finance, Economics, or related discipline required.
  • 1-3 years of analytical and/or data programming experience; consumer lending or credit card industry experience preferred.
  • Proficiency in SQL and at least one programming language (Python or SAS).
  • Strong quantitative and problem-solving skills
  • Strong work ethic with the ability to learn quickly and communicate effectively

Why Continental Finance?

Continental Finance Company (the “CFC”) is one of America’s leading marketers and servicers of credit cards for consumers with less-than-perfect credit. Since our founding in 2005, we have prided ourselves on corporate responsibility to customers in terms of a strong customer support program and fair treatment.  With our success, we have also grown into an innovative financial tech company! With a state-of-the-art consumer marketing and servicing platform, we provide a variety of services to consumers when other financial institutions will not accommodate them. With more than 2.6 million credit cards managed and serviced since our founding, we pride ourselves on putting the customer first. We are not a chartered banking financial institution, nor are we a debt originator or a credit card issuer.


CFC is an equal opportunity employer that is committed to inclusion and diversity. Our company provides equal employment opportunity (EEO) regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or veteran status.


CFC is seeking bright, energetic individuals that will help us grow and develop together! We uphold a promise to treat our employees with the same care and concern as we do our customers. We offer all employees competitive compensation and benefits in an exciting, fast-paced business casual environment. Join our growing team and apply online today!

 CFC offers a hybrid work schedule which includes three (3) core days in the office (Tuesday, Wednesday, and Thursday) and two (2) remote workdays (Monday and Friday)


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