Chief of Staff to the Chief Credit Officer
- Salary
- $265.2K–$419.4K
- Hiring from
- United States
- Work type
- Hybrid
- Posted
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Mulligan Funding is a San Diego based provider of funding to the Small and Medium Sized Business market. We are building a deeply researched and first-of-it’s-kind, Agentic AI complete funnel automation strategy. Mulligan has decades of deep credit underwriting and analytics expertise, combined with rich data from almost a million applications and billions of dollars funded via a wide loan size of $10k to $10 million. We are a mission-driven company, focused on solving the SMB market’s access to the fast and affordable capital they need to thrive by re-inventing how credit risk is measured, priced, and negotiated. We combine a generational-technology with unwavering integrity and a human touch.
Mulligan's ambition is to fundamentally reimagine small business lending — replacing legacy processes with AI-driven decisioning that is faster, smarter, and more accessible to small businesses. With 18 years of proprietary lending data, deep credit domain expertise, and AI capabilities already deployed and rapidly expanding across our core workflows, we have what most competitors cannot replicate: the institutional knowledge and the technical foundation to make that ambition real. We are looking for exceptional people who want to be at the center of that transformation — not watching it happen from the outside.
We have already made significant strides in our AI transformation, deploying production-grade AI agents across credit and underwriting workflows that deliver measurable results in speed, consistency, and decision quality. We are now accelerating that transformation across the full organization — bringing the same AI-first rigor to Sales, Customer Lifecycle, origination channel expansion, and progressively across every function in the business — while building an enterprise-grade AI product capability that scales.
We are seeking a Chief of Staff to work alongside our Chief Credit Officer every day. The Chief Credit Officer leads a broad part of the business, including data science across the company, credit strategy and portfolio analytics, fraud management, credit operations, collections and new partnership channels, and leads Mulligan's AI transformation program.
Within that program, the Chief Credit Officer owns the product design, the engineering and infrastructure design, and the roadmap for every capability the AI transformation builds. Most of this role's time will be spent there. You will work directly on that design and roadmap work, structuring decisions, testing designs before they are committed, and keeping a multi-workstream build on track, rather than observing it from a governance seat.
You will also be a thinking partner on strategy and product questions, the owner of the operating rhythm, and someone who can answer a data question directly rather than waiting in a queue for it. This is not a project-coordination role: it requires structured thinking, clear writing, and the confidence to bring a recommendation rather than a status update, and to push back with evidence when something does not add up.
The role reports to the Chief Credit Officer and is designed for someone early in their career, with three to five years' experience, who wants a front-row seat to how a lender is run and rebuilt, and who wants it to stretch them.
You Will
AI Transformation & Strategic Thinking Partnership
AI Transformation Design: Work alongside the Chief Credit Officer on product, architecture and roadmap decisions for the AI program: framing the trade-offs, testing designs against how the business actually works, and keeping the roadmap and its dependencies coherent.
Structured Problem Solving: Take a messy question, structure it, lay out the options with their trade-offs, and come back with a recommendation.
Pressure-Testing Ideas: Test proposals and plans before they go to the CEO, the leadership team or partners, and find the weak assumption before someone else does.
Analysis-Led Projects: Own discrete projects chosen by the Chief Credit Officer from across the remit, from framing the question through to a recommendation.
Operating Rhythm & Follow-Through
Priorities, Decisions & Actions: Maintain the weekly priorities, the decisions log and the action tracker across all the teams and partners the Chief Credit Officer works with.
Dependency Tracking: Keep commitments and dependencies across workstreams visible, with owners and due dates, and follow up until they are closed.
Recurring Reviews: Prepare the Chief Credit Officer's recurring reviews with product and program leads, and draft the regular executive update.
Data & Analysis
Self-Serve Analysis: Write SQL against the data warehouse and use Excel to answer funnel, portfolio and operational questions quickly: conversion, volumes, cycle times and roll rates.
Metric Discipline: Work from the company's agreed metric definitions, and reconcile any number going to senior leadership with the Data Science team first.
Honest Caveats: State what an analysis does and does not show. A number without its definition and limits is not finished.
Synthesis & Executive Communication
Briefings & Updates: Draft briefings, updates and presentation material, and turn long discussions into clear one-page summaries.
Meeting Preparation: Prepare the Chief Credit Officer for leadership and partner meetings: the context, the open questions and what is needed from the room.
Decision Capture: Attend senior meetings alongside the Chief Credit Officer, record the decisions and own the follow-up.
Cross-Functional Coordination
Internal Teams: Coordinate with leaders across credit, collections, data science and product on the Chief Credit Officer's behalf, working through influence rather than line authority.
External Partners: Work with technology and channel partners: prepare for their meetings, track commitments and make sure what was agreed actually happens.
You Bring
3-7+ years in product strategy, strategy and operations, management consulting, or a product or strategy analyst role.
SQL you use regularly on real, imperfect data (joins, aggregations and window functions) and strong Excel. You can build a quick analysis and explain what it does and does not show.
A track record of clear, structured written work, such as one-page summaries, briefing notes or decision memos, that senior people have acted on.
Experience working with senior colleagues and external partners: following up persistently and pushing back politely with evidence.
Sound judgment with confidential information.
Hands-on exposure to AI product work is strongly preferred: for example, scoping, designing or launching LLM-based or agentic products, or working on an AI transformation program. Data science or ML engineering experience on its own, without product or strategy work, is not a substitute.
Experience in lending, fintech or financial services or payment services, especially small-business related, is strongly preferred but not required. This role suits someone who brings a recommendation, not just a status report. Candidates whose experience is mainly project coordination or PMO reporting are unlikely to find the fit.
You Have
Structured Problem Solving: The ability to take an ambiguous question, break it into its parts, weigh the options and land on a recommendation, without being told what the answer should be.
Analytical Fluency: Comfortable pulling and shaping data in SQL and Excel, with Python a plus. Knows why a metric definition matters and spots when a number looks wrong before it travels.
Executive Writing: The ability to turn a long discussion or a complex topic into a one-page summary that a busy executive will read and act on.
Follow-Through & Influence: Polite persistence with senior people and partners. Keeps things moving without line authority, and is willing to push back with evidence.
AI Product Fluency: Working familiarity with how LLM-based and agentic products are designed, built and evaluated, enough to follow an engineering design discussion and ask the right questions. Deep technical expertise and credit expertise are not required.
A Bachelor's degree in Business, Economics, Engineering, Mathematics, Computer Science or a related quantitative field is required.
A MBA or Master's degree is a plus but evaluated secondary to demonstrated analytical, strategy and operations experience.
