Senior Data Scientist

Overview

As a Senior Data Scientist, you will independently develop data science solutions, machine learning models, and analytical insights that drive mission‑critical decisions across the organization. You will leverage member, financial, and operational data to identify opportunities for new products, services, and process optimization. This role requires strong communication skills to produce clear summaries, presentations, and documentation for leadership and cross‑functional partners. You will also collaborate closely with the Fair Lending, Compliance, and Model Risk Management team on model validations and remediation activities.

Responsibilities

• Design, develop, and evaluate moderately complex predictive models and advanced algorithms, with a strong focus on credit scoring.
• Identify meaningful insights from large datasets and metadata sources.
• Test hypotheses, analyze results, and interpret model performance.
• Develop and code moderately complex software programs, algorithms, and automated analytics pipelines.
• Present analytical findings, model results, and recommendations to senior management and internal stakeholders.
• Exercise sound judgment and discretion within established procedures and best practices.
• Ensure awareness of regulatory requirements-including Compliance and Fair Lending-and partner with relevant teams to validate models prior to implementation.
• Partner proactively with Model Risk Management on periodic model validations and remediation efforts.
• Create high‑quality written and verbal documentation, including model development, performance, and governance materials.
• Build strong working relationships with team members and subject matter experts.
• Lead small projects and cross‑functional initiatives.

• 5+ years of experience in exploratory data analysis, ideally including building tree‑based models.
• Strong programming and analytical skills, including experience with SQL, R, Python, SAS, and AWS.
• Understanding of financial services or banking concepts and regulatory considerations.
• Experience in model lifecycle execution, including development, monitoring, documentation, and governance.
• Experience validating models and partnering with internal or external auditors.
• Strong technical writing abilities, especially for model documentation.
• Excellent data storytelling and technical presentation skills.
• Strong research, analytical thinking, and problem‑solving abilities.
• Ability to work independently, critically evaluate your own work, and handle complex problems.
• Strong communication and interpersonal skills.
• Demonstrated ability to build collaborative relationships with internal and external partners.
• High initiative, sound judgment, and attention to detail.
• Technical proficiency in big data analytics, coding, project management, and technical writing.
• Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, or a related quantitative field.

• 5+ years of experience in financial services, particularly in acquisition model development, credit policy, or risk management.
• Master's or PhD in Data Science, Statistics, Mathematics, Computer Science, Engineering, or a related field.