Senior Decision Science Analyst

This is a fully remote position, open to applicants in Kansas.

📋 Description

• Create statistical and predictive models aimed at enhancing Credit and Fraud risk positions for both application and portfolio risk.

• Formulate risk and pricing strategies that integrate predictive models for Credit and Fraud.

• Assess the outcomes of risk and pricing strategies in relation to expectations.

• Develop tools for monitoring the ongoing performance of both standard and customized models.

• Access, cleanse, and analyze internal and external data for B2B credit risk management and pricing strategies pertaining to new account origination and existing account management.

• Deliver and present data-driven analyses to stakeholders and senior management, offering actionable insights.

• Perform data exploration, validation, and audits to pinpoint data quality issues and propose enhancements.

• Assist Engineering and Product teams in overcoming roadblocks and managing interdependencies.

⛳️ Requirements

• Bachelor’s Degree is required.

• A minimum of 6 years of demonstrated work experience in a highly analytical setting, conducting complex business analyses, generating data-driven insights, and presenting findings to leadership and stakeholders.

• Comprehensive knowledge of B2B credit and/or Business Banking credit risk, pricing, and profitability principles.

• Capability to navigate ambiguity and adapt workload in response to changing priorities.

• Proficiency in extracting, cleansing, merging, and analyzing data from diverse internal and external sources.

• Strong analytical and data simulation skills, including SAS and/or Python, MS Excel, Tableau/Sisense, or similar analytical and reporting/data visualization tools.

• Excellent presentation skills with proficiency in MS Word and PowerPoint.

• Experience in analyzing data segments or utilizing tools to identify and clarify patterns, trends, and/or process improvements.

• Ability to create clear and concise graphs, charts, reports, and presentations that summarize analytical results and justify recommended improvements.

• High-performing contributor with the capacity to collaborate cross-functionally with management, product, technology, compliance, and enterprise risk.

• Ability to manage multiple tasks in a fast-paced environment.

• Strong verbal and written communication skills.

• Preferred: Bachelor’s or Master’s Degree in Statistics, Mathematics, or a similar quantitative field of study.

• Preferred: Experience in statistical modeling (e.g., logistic regression, machine learning, SVM, etc.).

• Preferred: Previous leadership experience.

🏝️ Benefits

• Competitive salary.

• Paid parental leave.

• Generous paid time off.

• Medical, dental, vision, FSA, Life/AD&D, long and short-term disability options.

• 401K matching.

• Employee referral program.

• Reasonable accommodations for individuals with disabilities during the application and/or interview process.