Principal Data Scientist (Credit Risk for Small Business and Commercial)

Provide strategic data science, machine learning, and advanced analytics leadership to inform mission-critical decisions across the organization, with a primary focus on small business lending. Leverage small business credit, application, financial statement, cash flow, transaction, and performance data to shape underwriting, risk segmentation, pricing, portfolio management, and the end-to-end member lending experience. Partner with senior leaders and cross-functional stakeholders to identify high-impact opportunities, influence product and credit strategies, and translate complex data into scalable analytical solutions, actionable insights, and measurable business outcomes. Advance the organization’s analytical capabilities through descriptive, predictive, and prescriptive modeling and the responsible application of leading data science techniques. Operate as a trusted advisor and advanced practitioner, leading complex initiatives with broad independent judgment and developing analytical talent across the team.

- 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
- SQL, R, Python, Hadoop, SAS, 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

Desired Qualifications

- Master’s or doctoral degree in data science, statistics, mathematics, computer science, engineering, or a related quantitative discipline
- Demonstrated success applying data science, machine learning, or advanced analytics to small business banking, commercial lending, or small business lending strategies
- Deep experience designing and implementing analytical solutions across the lending lifecycle, including originations, underwriting, credit decisioning, pricing, account management, portfolio monitoring, and collections
- Strong command of small business credit risk, cash flow underwriting, commercial credit data, financial statements, transaction data, and alternative data sources
- Proven ability to influence senior leaders and partner across lending product, credit risk, underwriting, operations, and model risk to translate analytical insights into strategic business decisions

Additional Information

Hours:

- Monday - Friday, 8:00AM - 4:30PM

Location:

- 820 Follin Lane, Vienna, VA 22180