Vice President, Strategy & Analytics

• Take ambiguous questions from the CEO and turn them into structured investigations: define the hypothesis, pull the data yourself, test it, and develop a clear narrative.
• Write your own SQL queries within the company’s data and analytics tools (Sigma and Snowflake); this is a daily, non‑negotiable part of the job.
• Build and maintain the reporting the CEO needs to see the business clearly: originations, decisioning, funding, delinquency/DPD, early‑payoff, cash‑on‑cash and collection curves, cohort and vintage behavior, repeat vs. new customer performance, merchant and store performance, etc.
• Initially, focus on building a suite of portfolio risk reports (delinquency, charge‑off, vintage, and cohort performance) that give the CEO a real‑time view of how the book is performing.
• Trace anomalies to their root causes — segment by vintage, channel, merchant, score band, and decisioning change until you can explain what moved and why.
• Reconcile your numbers against what the functional teams report; when they differ, explain the delta.
• Synthesize findings into a clear narrative a busy CEO can act on, backed by data he can trust.

Requirements

• You personally write SQL (or equivalent) and are comfortable doing so every day — this is verified in the interview with a live analytical exercise.
• A combination of analytical rigor and clear communication.
• Strong working fluency in consumer credit and lending mechanics: vintages, first‑payment default, delinquency curves, cash‑on‑cash, cohort and repeat‑customer dynamics; lease‑to‑own or specialty consumer finance experience is a strong plus.
• Excellent judgement and an ability to escape and flag what you don’t know.
• You thrive as a party of one — you want proximity to hard problems, not a team to manage or a function to build.
• Likely backgrounds: strategic finance or biz‑ops at a lending or fintech company; PE or private credit analyst who codes; data analyst or scientist with consumer lending experience who writes well; ex‑consulting followed by a hands‑on, data‑heavy operating role.