Overview

The Credit Risk & Decision Science team within the Lending Analytics department is responsible for developing and implementing analytical solutions that drive changes to underwriting policies across Navy Federal Credit Union's various lending products. Data scientists within this team will focus on two areas. Firstly, they will leverage analytics to define and monitor credit card account management strategies such as proactive line increase and reactive line increase to name a few. This will include developing and recommending test and control strategies to better understand cardholder behavior. Secondly, data scientists will leverage the existing pricing framework to support rate changes across various lending portfolios. Successful candidates will exhibit effective communication and analytical skills as well as strong leadership qualities.

• 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
• Transform data into charts, tables, or format that aids effective decision making
• 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 lower levels

• 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

• Familiar with analytical frameworks used to support the pricing of lending products
• Familiar with analytical models/analysis used to support credit card underwriting and account management underwriting policies
• Familiar using GitHub for documentation and code collaboration purposes
• Master's/PhD Degree in Data Science, Statistics, Mathematics, Computers Science, or Engineering