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Credit Risk Data Science Jobs in Washington (NOW HIRING)

PTR Global

Senior Credit Risk Analyst

Mclean, VA · On-site

$65 - $70/hr

This role requires expertise in data processing, analytics, and reconciliation across multiple systems, with a strong focus on mortgage credit risk and market risk management. The ideal candidate ...

Visa

Director, VCA NA Risk Practice

Ashburn, VA · On-site

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 ...

Fannie Mae

Data Science Advisor

Washington, DC

Apply data science to improve risk measurement, valuation, decision-making, and business performance. * Create technical strategies and executive-ready materials that communicate high-impact ...

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Credit Risk Data Science information

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.
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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:
Credit Risk Data Science jobs near you
Credit Card Risk & Policy Director - McLean, VA

Credit Card Risk & Policy Director - McLean, VA

Veritas Partners

Mclean, VA

Full-time

Posted 13 days ago

Job description

Responsibilities
Manage and grow a team with strong analytical and credit strategy development capability, focusing on credit risk and portfolio/account level profitability, as well as optimizing marketing effectiveness.
  • Lead team to develop and manage new origination automated/judgmental credit strategies as well as account management credit policies, from approve/decline, line assignment and portfolio risk management.
  • Responsible for defining Credit Card strategy risk tolerance limits and decisioning constraints in collaboration with second line Credit Risk Management.
  • Lead team to develop and maintain cash flow/NPV valuation tool for acquisition and account management programs to enable decisioning optimization.
    • Derive and refine risk segmentation and loss expectations / risk premium.
    • Ground and extrapolate economics inputs, assumptions, and curve shape.
    • Evaluate, recommend, and operate valuation platform.
    • Automate sensitivity and gaming functionalities.
    • Develop standardized metrics and reporting around NPV valuation, monitoring, and platform/tool assessment/refinement.
    • Working with finance to govern the NPV development, review and decision-making process.
  • Lead team to develop / refine Credit Card initial line assignment strategy:
    • Evaluate and recommend segmentation schemes, such as Risk, Channel, Product, Channel and Ability to Pay.
    • Derive recommended initial credit limit based on cash flow valuation model economics projections and decision constraints. Benchmark against industry.
    • Ground sensitivities on assumption for line assignments and testing agenda for continuous optimization.
    • Develop and test on graduation / line increase strategy (with control and assumptions needed for the program to be effective)
  • Lead team to develop credit strategies tailored to acquisition channel and product type to support business growth. Partner with business segment product owners to optimize acquisition targeting/marketing campaigns that align with credit policies.
  • Lead team to monitor credit quality, risk performance, and economics of Credit Card & Overdraft portfolio on the ongoing basis to prevent or mitigate consumer loan losses.
    • Program deep dive and credit policy change monitoring to drive credit policy optimization and risk mitigation strategies.
    • Monitoring and analysis of credit risk for both organic and acquired portfolio, prepare materials for regular Business Review and Credit Risk Committee presentation.
  • Provide risk analytics to support credit expansion by overseeing credit aspects of onboarding of acquired portfolios and product launch.
  • Function as a strategic and trusted partner with Product Team as they evaluate new asset classes/products.
  • Identify required data and work with data stewards to understand data source, ensure data quality and retrieve data on a timely basis. Contribute to credit data mart and corporate database designs.

Qualifications:
Bachelor’s degree in business, Economics, Quantitative Discipline or Equivalent, Finance is required. MBA or master’s degree in the related field is highly preferred.
  • 12+ years’ experience in credit strategy, credit policy & analysis or credit risk management in the financial services industry. Experience in Consumer Lending products preferably Credit Card.
  • Minimum of 5+ years of direct management experience.
  • Ability to interact effectively with a variety of partner teams within and outside Consumer Banking in a collaborative environment. Ability to influence and build consensus with 2nd line Credit Risk on credit decisions.
  • Detail-oriented, results-driven, and ability to navigate in a quickly changing and high demand environment to develop solutions while balancing multiple priorities.
  • Demonstrate strong integrative thinking, problem-solving and high degree of proficiency in synthesizing and communicating data from a variety of disciplines.
  • Excellent written, verbal communication and presentation skills. Ability to explain complex topics and technical details in succinct storytelling to a wide variety of audiences.
  • Self-motivated and strong people skills to actively lead and implement ideas in a cross-functional team environment.
  • Proven project management skills, ability to manage multiple projects. Ability to manage multiple projects simultaneously and adapt to rapid changes in priority.
  • Strong skills in various data analysis and visualization tools including PowerPoint, Excel, Tableau and SQL are required.
Experience using A.I. tools preferred.