Director, Credit Portfolio Analytics

•             Portfolio Governance: Define corporate credit policy, exposure limits, and risk tolerance models for a multi-million/billion-dollar trade credit and receivables portfolio.

•             Executive Advisory: Deliver high-impact briefings, predictive forecasts, and strategic recommendations directly to Executive Leadership on portfolio credit quality, delinquency trends, and exposure concentrations.

•             Enterprise Risk Management: Monitor macro-level credit, counterparty, and financial risks across the entire trade credit ecosystem, including seller and buyer concentration, industry exposure, and macroeconomic sensitivity.

•             Team Leadership: Develop, direct, and upskill a high-performing team of credit and portfolio analysts, establishing data standards and analytical best practices.

•             Advanced Modeling: Personally design, build, and maintain sophisticated, scalable credit risk and predictive models (e.g., loss forecasting, probability of default, roll-rate, vintage analysis) to evaluate portfolio performance.

•             Deep-Dive Analytics: Write complex data queries and code to extract, manipulate, and analyze large datasets from disparate corporate systems, including receivables, collections, and underwriting platforms.

•             Root-Cause Diagnostics: Step in to troubleshoot data anomalies, audit complex credit loss and delinquency calculations, and validate the underlying logic of team-generated reports.

•             Dashboard Architecture: Support and maintain executive-level dashboards and visualization architectures tracking portfolio health, delinquency, and credit risk KPIs using enterprise BI tools.

•             12+ years of progressive experience in trade credit, credit risk management, corporate finance, or B2B receivables/portfolio management, with a proven track record of blending strategy with technical execution.

•             Bachelor’s degree in Statistics, Mathematics, Finance/Economics or similar quantitative field of study

•             Expert-level proficiency in advanced Excel, SQL, and data programming languages (SAS or Python).

•             Experience supporting the development of data models and visualizations within Enterprise BI tools.

•             Exceptional ability to translate dense, highly technical analytical findings into clear, actionable business narratives for non-technical stakeholders.

•             Master’s Degree in Statistics, Mathematics, Finance/Economics or similar quantitative field of study

•             Strong knowledge of B2B and/or Business Banking credit product pricing and profitability principles

•             Statistical modeling experience (logistic regression, machine learning, SVM, and more)

•             Prior leadership/management experience

• Competitive salary
• Paid parental leave
• Generous paid time off
• Medical, dental, vision, FSA, Life/AD&D, long and short term disability
• 401K matching
•  Employee referral program

• in saying yes to unique and challenging requirements
• empowered team members are creative team members
• our products make the customer’s day just a little bit better
• work/life balance makes us all more effective