Senior Data Scientist (Underwriting Credit Policy)

Overview

Provide independent data science, machine learning, and analytical insights using member, financial, and organizational data to mitigate credit risk while driving origination growth. Understand business needs and identify opportunities to reduce credit risk and prevent lending losses for new and existing products to meet business objectives. Drive strategic insights in risk management, loss forecasting, and stress testing impacts across the organization through descriptive, predictive, and prescriptive models. Conduct complex work assignments using cutting-edge data science under moderate supervision to enhance analytics infrastructure and deliver actionable insights.

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• Design, develop, and evaluate moderately complex predictive models and advanced algorithms
• Identify meaningful insights from large data and metadata sources
• Test hypotheses/models, analyze, and interpret results
• Create reporting and analytics functions to evaluate and mitigate credit risk within lending businesses.
• Exercise sound judgment and discretion within defined procedures and practices
• Develop and code complex software programs, algorithms, and automated processes
• Use modeling and trend analysis to analyze data and provide insights
• Develop understanding of best practices and ethical AI
• Transform data into actionable insights using data visualization tools that aids effective decision making
• Build working relationships with team members and subject matter experts
• Lead small projects and initiatives
• Utilize effective written and verbal communication to document and present findings of analyses to a diverse audience of stakeholders

• 3-5 years of experience in exploratory data analysis
• Understanding of account acquisition, portfolio management, underwriting strategy, credit line strategy, pricing strategy, collection strategy
• Basic understanding of business and operating environment
• Statistics
• 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
• Working 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.)
• Sound Judgment
• Problem Solving (Responds as problems and issues are identified)
• Bachelor's Degree in Data Science, Statistics, Mathematics, Computers Science, Engineering, or degrees in similar quantitative fields

• Master's/PhD Degree in Data Science, Statistics, Mathematics, Computers Science, or Engineering