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Credit Risk Data Science Jobs in Maryland (NOW HIRING)

... credit risk, market risk, liquidity risk, and operational risk. Evaluate model assumptions, data ... Bachelor's Degree in Arts/Sciences (BA/BS) or advanced degree in finance, economics, mathematics ...

... credit risk, market risk, liquidity risk, and operational risk. Evaluate model assumptions, data ... Bachelor's Degree in Arts/Sciences (BA/BS) or advanced degree in finance, economics, mathematics ...

Manage the ongoing credit risk of existing loan portfolios through continuous credit monitoring ... Enter complete and accurate data into Bank systems in support of underwriting and portfolio ...

Manage the ongoing credit risk of existing loan portfolios through continuous credit monitoring ... Enter complete and accurate data into Bank systems in support of underwriting and portfolio ...

Manage the ongoing credit risk of existing loan portfolios through continuous credit monitoring ... Enter complete and accurate data into Bank systems in support of underwriting and portfolio ...

Data Scientist

Fort George G Meade, MD · On-site

$156K - $176K/yr

Early data science input during IOC ensures that data collected will be suitable for downstream AI development, reducing risk and accelerating capability maturation during follow-on implementation

Conduct scenario analysis, what-if studies, optimization, and risk analysis. * Interpret simulation ... Master-level data science industry knowledge and knowledge of the insurance marketplace. What would ...

Conduct scenario analysis, what-if studies, optimization, and risk analysis. * Interpret simulation ... Master-level data science industry knowledge and knowledge of the insurance marketplace. What would ...

... Credit Risk Monitor reporting services. The RCM will synthesize such external data with internal profit profile data to determine and recommend optimal credit terms and then convey those ...

$99K - $225K/yr

... science techniques and met hods and leverage a suite of data-driven tools to aid the client's service leadership and subject matter experts to increase decision space, understand strategic risk, and ...

Showing results 21-40

Credit Risk Data Science information

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.

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 job categories do people searching Credit Risk Data Science jobs in Maryland look for?

The top searched job categories for Credit Risk Data Science jobs in Maryland are:

What cities in Maryland are hiring for Credit Risk Data Science jobs?

Cities in Maryland with the most Credit Risk Data Science job openings:

Model Risk Management Officer

EagleBank

Bethesda, MD • Hybrid

$152K - $261K/yr

Full-time

Medical, Retirement

Posted 5 days ago


Job description

Overview

We are a values driven organization putting Relationships FIRST. EagleBank (NASDAQ - EGBN) is focused on being Flexible, Involved, Responsive, Strong, and Trusted. By prioritizing meaningful connections with our customers, employees, and shareholders, we relentlessly deliver the most compelling, valuable service to our customers.EagleBank is committed to inclusion, equity, and respect. We celebrate diversity and intentionally seek out opportunities to learn from one another's experience. We believe employees are essential to the building of relationships and we prioritize investing in employee growth and wellbeing. Employee involvement is fostered through resource groups, mentorship programs, community service, and scholarship opportunities for continued education. With features including maternity and parental leaves, wellness discounts, healthcare premium sharing, employer funding in your HSA account, and 100% 401(k) matching up to 4%, we pride ourselves in the ways we support our internal relationships. The minimum and maximum projected annualized salary for this position is: $152,662.00 to $261,706.80. Additional compensation may be possible based on experience and skills.

We understand the need to be creative and flexible when it comes to telecommuting and other alternative work arrangements. This position is eligible for our hybrid remote work and will work in the Bethesda, MD office four days per week.

Responsibilities

The Model Risk Management Officer is the Bank's second-line expert for model risk and quantitative financial risk analytics, administering model inventory, risk assessments, validation, monitoring, governance, issue management, and regulatory reporting. The role also provides independent review and advice on stress testing, scenario analysis, CECL, portfolio and concentration risk, capital planning, liquidity risk, and related quantitative practices. This role partners with Finance, Treasury, Credit Risk, Internal Audit, Compliance, executive management, and regulators to ensure models and quantitative tools are appropriately governed, validated, monitored, and used

Essential Function:

  • Model Validation: Perform rigorous model validation to ensure the accuracy, robustness, and appropriateness of the bank's models. Review and validate models across different areas, including credit risk, market risk, liquidity risk, and operational risk. Evaluate model assumptions, data integrity, calibration, and performance, and provide recommendations for improvement when necessary.
  • Financial Risk Analytics and Advisory: Partner to provide review of stress testing methodologies, scenario analyses, assumptions, and results used across capital planning, liquidity risk management, CECL, concentration risk management, and portfolio risk assessment activities.
  • Risk Assessment: Analyze and assess the risks associated with the bank's models, including model limitations, data quality, and model assumptions. Identify potential model risks and develop risk mitigation strategies and controls to minimize the bank's exposure to model-related risks. Stay up to date with industry best practices and regulatory requirements related to model risk management.
  • Documentation and Reporting: Prepare comprehensive reports documenting the findings of model validation activities. Clearly communicate the results, including identified model risks and recommended actions, to senior management, risk committees, and regulatory authorities. Ensure the accuracy and completeness of documentation in compliance with internal policies and regulatory guidelines.
  • Collaboration and Stakeholder Management: Collaborate effectively with various stakeholders, including quantitative modelers, risk managers, senior management, and internal audit teams. Provide guidance and support to other teams in understanding and addressing model risk issues. Participate in meetings, committees, and working groups related to model risk management
  • Continuous Improvement: Proactively identify opportunities for enhancing the bank's model validation practices. Recommend and implement improvements in methodologies, processes, and tools used for stress testing and model validation. Stay abreast of emerging trends, industry standards, and regulatory changes in model risk management.
Qualifications

Requirements:

  • Bachelor's Degree in Arts/Sciences (BA/BS) or advanced degree in finance, economics, mathematics, statistics, or a related quantitative field
  • 8 years of experience in model risk management within the financial services industry, with a strong focus on stress testing and model validation
  • Demonstrated experience supporting financial risk analytics including stress testing, scenario analysis, credit portfolio analytics, capital planning, liquidity risk management, CECL methodologies, and concentration risk assessment within a financial institution
  • Able to model, analyze, identify, and communicate risk
  • Proficiency in statistical modeling, risk assessment techniques, and model validation principles
  • Familiarity with financial products, risk management frameworks, and Basel guidelines
  • Excel expertise - truly the highest level of excel user
  • Strong analytical and critical thinking skills, with the ability to think critically and independently
  • Excellent written and verbal communication skills, with the ability to convey complex concepts to both technical and non-technical stakeholders
  • Strong knowledge of the Interagency Model Risk Management Guidance (FRB SR 26-2 / OCC Bulletin 2026-13), foundational SR 11-7 model risk management principles, guidance related to CECL, capital planning, liquidity risk management, stress testing, and third-party model oversight

Preferences:

  • Familiarity with with Python, R, SQL, SAS, or similar analytical tools
  • Professional certifications such as FRM (Financial Risk Manager) or CFA (Chartered Financial Analyst) are advantageous

Don't meet all the requirements? We encourage you to still apply if you think you are the right person to join our community. We are always interested connecting with people inspired by our mission and values. If you aren't hired for this position, your resume will remain available for the next year and might be considered for future openings. Note: You can update your resume as often as needed.

Employment Type: OTHER