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Credit Risk Data Science Jobs in Philadelphia, PA

M&T Bank

CRE Commercial Credit Associate

Radnor, PA

Manage the ongoing credit risk of existing loan portfolios through continuous credit monitoring ... data. Determine the need for more thorough investigation or additional information. * Analyze ...

M&T Bank

CRE Commercial Credit Associate

Radnor, PA · On-site

Manage the ongoing credit risk of existing loan portfolios through continuous credit monitoring ... data. Determine the need for more thorough investigation or additional information. * Analyze ...

Lincoln Financial

Databricks Engineer and Architect

Radnor, PA · On-site

$58.50 - $76.75/hr

... risk, credit risk, and operational risk data on the enterprise scale. Significant Databricks ... What we're looking for • Bachelor's degree in Computer Science, Information Systems, Engineering ...

Td

Data Scientist III - FCRM Risk Modeling

Wilmington, DE · On-site

$96K - $155K/yr

... data analysis related material. Department Overview: The US Financial Crime Risk Modeling ... science) Graduate's degree preferred with either progressive project work experience or * 5+ year ...

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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 Jul 27, 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 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 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 July 2026, with employment types broken down into 85% Full Time, 14% Part Time, and 1% Contract. Highlights an 95% Physical, 1% Hybrid, and 4% Remote job distribution, with an average salary of $114,916 per year, or $55.2 per hour.
Quantitative Analytics Lead- Model Risk Management

Quantitative Analytics Lead- Model Risk Management

OneMain Financial

Wilmington, DE • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

This job post has expired today. Applications are no longer accepted.

OneMain Financial rating

7.6

Company rating: 7.6 out of 10

Based on 100 frontline employees who took The Breakroom Quiz

111th of 150 rated financial services

Job description

Quantitative Analytics Lead- Model Risk Management
Location: Wilmington, DE (Hybrid)
OneMain is seeking a Quantitative Analytics Lead, Model Risk Management (MRM) to help lead and strengthen the firm's Model Risk Management program in alignment with regulatory guidance, including SR 11-7 and OCC supervisory expectations. This role supports a diverse consumer credit portfolio, including Personal Loans, Credit Cards, Automotive, and Point-of-Sale lending.
The position offers a unique opportunity to apply advanced analytics and machine learning expertise while exercising independent challenge across the full model lifecycle. The role also plays a key part in regulatory readiness, audit engagement, and the continued evolution of OneMain's Fair Lending analytical governance framework.
Responsibilities
  • Provide hands-on model governance oversight across the full model lifecycle, including development, implementation, validation, use, and ongoing monitoring of machine learning models supporting marketing, origination, servicing, and loss mitigation.
  • Perform independent and effective challenge of models, assessing conceptual soundness, data integrity, methodology, assumptions, and limitations. Evaluate key development decisions, including target construction, training versus validation strategies, sampling approaches, performance windows, hyper-parameter tuning, model performance metrics, variable selection, and swap-set analyses.
  • Provide robust challenge and governance oversight of CECL and loss forecasting models, serving as a central point of contact for internal audit, external audit, and regulatory examinations. Prepare clear, well-supported model governance and validation documentation in support of model approvals and ongoing use.
  • Conduct periodic model validations and assess whether validation activities performed by internal teams or third parties meet Model Risk Management policy requirements, including outcomes analysis, benchmarking, and sensitivity testing, as appropriate.
  • Apply analytics, business rules, and other risk tools to monitor model performance and behavior, identify emerging risks or anomalies, and recommend remediation or model enhancements when warranted.
  • Contribute to the ongoing modernization of the MRM function by leveraging advanced analytics and AI-enabled tools to improve governance efficiency, documentation quality, and knowledge management.
  • Participate in broader artificial intelligence and advanced analytics initiatives in partnership with the data science & technology organization, ensuring appropriate governance and risk controls are embedded from inception.
  • Support OneMain's Fair Lending Analytics Program by developing fair lending models and conducting statistically rigorous analyses to assess potential disparate impact and compliance risk.
  • Apply regression, classification, and related statistical techniques to perform deep-dive analyses, clearly articulating both statistical and practical significance to inform risk decisions and regulatory communications.

Qualifications
  • Master's degree in a quantitative discipline (Statistics, Mathematics, Data Science, or related field) required; PhD preferred.
  • 3+ years of experience in statistics, data science, decision science, or a related quantitative field.
  • 3+ years of experience building, reviewing, or validating machine learning models within the consumer finance industry.
  • Strong understanding of consumer lending products, credit risk practices, and regulatory expectations related to model risk management.
  • Hands-on experience with machine learning techniques, particularly tree-based models such as XGBoost, and strong analytical "deep-dive" capabilities.
  • Exposure to modern AI concepts, including Generative AI, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG) systems, with an appreciation for associated governance and risk considerations.
  • Proven ability to lead and manage complex, ambiguous projects and provide structured, defensible analytical judgment.
  • Strong written and verbal communication skills, with the ability to explain complex technical concepts to non-technical stakeholders, auditors, and regulators.
  • Demonstrated intellectual curiosity, strong idea generation, and an interest in research, innovation, and continuous improvement.
  • Proficiency in Python and SQL; experience with AWS and SageMaker is a strong plus.

Who We Are
OneMain Financial (NYSE: OMF) is the leader in offering nonprime customers responsible access to credit and is dedicated to improving the financial well-being of hardworking Americans. Since 1912, we've looked beyond credit scores to help people get the money they need today and reach their goals for tomorrow. Our growing suite of personal loans, credit cards and other products help people borrow better and work toward a brighter future.
Driven collaborators and innovators, our team thrives on transformative digital thinking, customer-first energy and flexible work arrangements that grow lives, careers and our company. At every level, we're committed to an inclusive culture, career development and impacting the communities where we live and work. Getting people to a better place has made us a better company for over a century. There's never been a better time to shine with OneMain.
Because team members at their best means OneMain at our best, we provide opportunities and benefits that make their health and careers a priority. That's why we've packed our comprehensive benefits package for full- and some part-timers with:
  • Health and wellbeing options including medical, prescription, dental, vision, hearing, accident, hospital indemnity, and life insurances
  • Up to 4% matching 401(k)
  • Employee Stock Purchase Plan (10% share discount)
  • Tuition reimbursement
  • Paid time off (15 days' vacation per year, plus 2 personal days, prorated based on start date)
  • Paid sick leave as determined by state or local ordinance, prorated based on start date
  • Paid holidays (11 days per year, based on start date)
  • Paid volunteer time (3 days per year, prorated based on start date)

OneMain Holdings, Inc. is an Equal Employment Opportunity (EEO) employer. Qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship status, color, creed, culture, disability, ethnicity, gender, gender identity or expression, genetic information or history, marital status, military status, national origin, nationality, pregnancy, race, religion, sex, sexual orientation, socioeconomic status, transgender or on any other basis protected by law.

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