Principal Data Scientist (Credit Risk Forecasting)

Location: Hybrid role based in Vienna, Virginia, or Pensacola, Florida, United States. Monday–Friday, 8:00 AM–4:30 PM. Applicants must be authorized to work in the United States without current or future sponsorship.

Salary: $114,500–$179,500 annually.

Company

A large credit union providing financial products and services, with a focus on consumer lending, credit risk management, and member financial outcomes.

What you will do

• Develop, implement, execute, monitor, document, and govern CECL models for consumer lending portfolios.
• Design, develop, test, and evaluate complex predictive models, algorithms, and advanced statistical solutions.
• Analyze high-dimensional datasets to produce actionable insights and recommendations for mission-critical decisions.
• Develop complex software programs and automated analytical processes using data science and machine learning techniques.
• Lead moderate to large projects, collaborate with stakeholders and senior management, and present technical findings.
• Serve as a technical resource and mentor junior staff in credit risk forecasting and financial performance assessment.

Requirements

• 6+ years of relevant experience and a bachelor's degree in data science, statistics, mathematics, computer science, engineering, or a related quantitative field.
• Advanced knowledge of statistics, machine learning, data mining, data modeling, simulation, advanced mathematics, and data visualization.
• Experience with Python, R, SAS, SQL, Hadoop, SPSS, Scala, and AWS.
• Knowledge of model lifecycle execution, validation techniques, technical writing, data storytelling, and technical presentations.
• Must be authorized to work in the United States without current or future sponsorship.
• Strong independent judgment, critical thinking, problem-solving, communication, project leadership, and collaboration skills.

Nice to have

• Master's or PhD in data science, economics, statistics, mathematics, computer science, engineering, or a related field.
• Advanced knowledge of CECL reserving, credit loss forecasting, and Model Risk Management guidelines.
• Experience with consumer lending portfolios and loan-level or account-level credit loss models, including probability of default, loss given default, exposure at default, prepayment, survival, hazard, or competing risk models.
• Experience with controlled model production, version control, validation, reconciliation, monitoring, documentation, change management, and audit or regulatory reviews.
• Knowledge of banking trends, credit cycles, portfolio performance drivers, reserve implications, and applicable lending regulations.

Culture & Benefits

• Meaningful career experience in an energized, engaged, and mission-focused environment.
• Competitive pay and generous benefits and perks.
• Opportunities to mentor colleagues and contribute to organizational capability development.
• Commitment to ethical AI, professional development, and strong working relationships.