Principal Data Scientist (Credit Risk Forecasting)
- Discuss this with your agent
- Open in Claude
- Open in ChatGPT
Prepare application
- Draft this with your agent
- Open in Claude
- Open in ChatGPT
Role details
Tech stack
+9 more
Job description
- Contribute to the end-to-end CECL model development, implementation, execution, monitoring, documentation, and governance for consumer lending portfolios
- Design, develop, and evaluate large and complex predictive models and advanced algorithms
- Test hypotheses/models, analyze, and interpret results
- Develop actionable insights and recommendations
- Develop and code complex software programs, algorithms, and automated processes
- Use evaluation, judgment, and interpretation to select right course of action
- Work on problems of diverse scope where analysis of information requires evaluation of identifiable factors
- Produce innovative solutions driven by exploratory data analysis from complex and high-dimensional datasets
- Utilize effective written and verbal communication to document analyses and present findings analyses to a diverse audience of stakeholders
- Develop and maintain strong working relationships with team members, subject matter experts, and leaders
- Lead moderate to large projects and initiatives
- Model best practices and ethical AI
- Works with senior management on complex issues
- Assist with the development and enhancement practices, procedures, and instructions
- Serve as technical resource for other team members
- Mentor the junior team members, providing guidance on both credit risk forecasting and financial performance assessments to develop talent and enhance organizational capabilities.
Requirements
Navy Federal Credit Union currently does not provide sponsorship for this role. Applicants must be authorized to work in the United States without the need for current or future sponsorship.
Developing and deploying NFCU Lending CECL and credit risk predictive models, post-model adjustment, advanced analytics, and advanced statistical techniques, solutions and actionable insights that deliver business impacts. Provide independent data science, machine learning, and analytical insights using member, financial, and organizational data to support mission critical decision making for various areas of the organization. Create descriptive, predictive, and prescriptive models and insights to drive impact across the organization. Regarded as an advanced professional in the data science field. Conduct complex work under minimal supervision and with wide latitude for independent judgment. Mentor lower level staff., * 6+ years of experience with requisite competencies
- Complete knowledge and full understanding of specialization
- Statistics, machine learning, data mining, data auditing, aggregation, reconciliation, and visualization
- Programming, data modeling, simulation, and advanced mathematics
- Python, R, SAS, SQL, Hadoop, SPSS, Scala, AWS
- Model lifecycle execution
- Technical writing
- Data storytelling and technical presentation skills
- Research Skills
- Interpersonal Skills
- Advanced knowledge of procedures, instructions and validation techniques
- Model Development
- Communication
- Critical Thinking
- Collaborate and Build Relationships
- Initiative with sound judgement
- Technical (Big Data Analysis, Coding, Project Management, Technical Writing, etc.)
- Independent Judgment
- Problem Solving (Identifies the constraints and risks)
- Bachelor’s Degree in Data Science, Statistics, Mathematics, Computers Science, Engineering, or degrees in similar quantitative fields, * Master’s/PhD Degree in Data Science, Economics, Statistics, Mathematics, Computers Science, or Engineering
- Advanced knowledge of CECL reserving, credit loss forecasting, and Model Risk Management guidelines.
- Experience with consumer lending portfolios such as credit card, auto, secured consumer lending, unsecured consumer lending, mortgage, or home equity.
- Familiarity with loan-level or account-level credit loss modeling techniques, including probability of default, loss given default, exposure at default, prepayment, survival/hazard, and competing risk models.
- Experience implementing controlled model production processes, including version control, data validation, reconciliation, monitoring, documentation, and change management.
- Experience responding to Model Risk Management validation, internal audit, external audit, regulatory, accounting, or control review questions.
- Advanced knowledge of applicable federal and state laws, rules, and regulations that govern credit card, secured consumer lending, and unsecured consumer lending.
- Advanced knowledge of banking and financial industry trends, products, services, credit cycles, portfolio performance drivers, and reserve implications.
About the company
Navy Federal provides much more than a job. We provide a meaningful career experience, including a culture that is energized, engaged and committed; and fierce appreciation for our teams, who are rewarded with highly competitive pay and generous benefits and perks.
Our approach to careers is simple yet powerful: Make our mission your passion.
FORTUNE 100 Best Companies to Work For 2026
Yello and WayUp Top 100 Internship Programs 2025
Computerworld Best Places to Work in IT 2026
Most Loved Workplace - America’s Top Most Loved Workplaces 2025
2025 PEOPLE Companies That Care
Newsweek Most Trustworthy Companies in America 2026
Apply for this position
This job is hosted externally. Click below to view the full posting and apply.
Prepare application
- Draft this with your agent
- Open in Claude
- Open in ChatGPT
Good distractions
Talks and stories from around this role — technically off-topic, practically not.
Moments
Explore playlistsVideos
See allRelated articles
See all
Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production
Data Analyst Salary in Switzerland
Highest Paying Tech Companies for Developers
Résumé-Driven Development: How IT trends affect the job market for software developers