FP&A Manager, GTM Finance - Credit Products

Focus on Marqeta's credit business by partnering with Sales, Legal, Product, Credit Risk, and Capital Markets to model pricing, evaluate profitability, and structure deals that win business while protecting unit economics. Flex in on debit and prepaid as needed, but credit will be your primary focus. Credit deals involve distinct revenue mechanics, cost structures, and stakeholders—modeling them requires understanding life-of-loan economics, vintage performance, capital efficiency, and revenue share splits across multiple parties.

A key part of this role is partnering with Marqeta's credit function to build financial models that help secure new bank partnerships and capital providers. You’ll craft projections, scenario analyses, and economic narratives for prospective partners. You won’t just forecast—you’ll be in the room with Sales, shaping deals in real time by pressure-testing assumptions on interchange splits, loss curves, and program economics. Join a tight-knit deal desk team that shares context, wins, and the workload. The pace is fast, and the team is how we keep up.

This role can be performed remotely anywhere within the U.S. or from our Oakland office.

Impact You'll Have

• Serve as the financial partner to Sales on live credit deals—modeling the full economic stack: interchange, finance charges, fees, rewards costs, cost of funds, expected losses, network fees, and sponsor bank revenue share.
• Build deal-level models that capture full life-of-portfolio economics, not just first-year interchange, but how the deal performs as the portfolio matures, revolve rates stabilize, and losses curve in.
• Partner with Credit Risk and Capital Markets teams to ensure every deal model reflects realistic loss assumptions, funding costs, and capital efficiency considerations.
• Collaborate with the credit function to build foundational models for credit products, including monthly projections of volumes, receivables, payment rates, and loss curves with clearly defined assumptions tied to industry and internal data. Develop scenario analyses to support acquiring new bank partnerships and capital providers (warehouse facilities, return-on-capital projections, portfolio performance scenarios).
• Model multi-party revenue share structures across program manager, sponsor bank, processor, and network—and stress-test how splits behave at different volume and performance tiers.
• Lead deal review meetings on credit deals with sales leadership, translating complex credit economics into clear, actionable recommendations that help close business without compromising margin.
• Build and continuously sharpen the credit-specific deal desk toolkit—pricing benchmarks, loss-curve templates, capital-cost calculators, vintage performance models, and dashboards that bring them together.
• Help Sales speak credibly about credit economics with prospects, from sophisticated fintech buyers to commercial customers exploring credit products for the first time.
• Stay close to credit product evolution, regulatory developments (Reg Z, CFPB, state usury), and competitive dynamics in the credit issuing space—and bring that intelligence into every deal.
• Collaborate with the deal desk team across debit, prepaid, and other product lines—flexing in when needed, sharing knowledge, and raising the bar together.
• Experiment with AI to make credit deal modeling faster and better—automating portfolio projection models, accelerating scenario analysis, or building internal tools that scale your judgment across more deals.

Requirements

• Bachelor's degree in a quantitative field—Finance, Accounting, Economics, Engineering, Math, or a discipline that built your numerical fluency.
• 6-8 years of experience in financial planning and analysis, deal desk, pricing, credit product finance, or a related GTM finance function—with meaningful exposure to credit card or lending economics.
• Comfortable across the credit economics stack. You understand how interchange, finance charges, rewards funding, loss provisioning, and cost of funds combine into deal-level economics. Vintage curves, charge-off rates, and revolve behavior are familiar concepts.
• An exceptional partner and team player. You build trust quickly with Sales, push back without friction, jump in when teammates are slammed, and treat wins as collective rather than individual. You’re the person other teams want in the room when a credit deal gets complicated.
• A genuinely strong financial mind. You’re fluent in modeling, comfortable with ambiguity in the numbers, and knowledgeable about credit risk modeling and capital markets concepts to be a credible partner to those teams.
• Thrive under pressure. Credit deals don’t wait, and they don’t simplify. You’re energized by a fast pace, multiple priorities, and the occasional fire drill—and you deliver accurate work even when the clock is loud.
• AI-curious and hungry to experiment. You already use AI tools in your day-to-day work, have opinions about what’s overhyped and what’s useful, and see AI as leverage to do more—not a threat or checkbox.
• Excellent written and verbal communicator—you can take a messy credit deal structure with five moving parts and turn it into a one-slide answer for an executive.
• Proactive, with a bias toward improving processes rather than tolerating them.
• Advanced Excel; comfortable across Google Workspace.

Nice-To-Haves

• Direct experience pricing or modeling credit card programs—issuer side strongly preferred.
• Background at a credit card issuer, fintech with a credit product, BIN sponsor bank, or program manager.
• Familiarity with BIN sponsorship economics and direct bank partnership structures.
• Experience building financial models used to pitch sponsor banks, capital providers, or warehouse lenders—including portfolio projections, return-on-capital analyses, and scenario modeling.
• Working knowledge of credit risk modeling concepts: expected loss, vintage analysis, behavioral scoring.
• Working knowledge of capital markets concepts relevant to credit card receivables: warehouse facilities, securitization, cost of funds.
• Familiarity with credit card regulatory framework (Reg Z, CFPB requirements, state usury considerations).
• SQL / data analytics experience, especially Snowflake.
• Hands-on experience building workflows or tools with AI (custom GPTs, agents, automations, prompt engineering for finance use cases).

Pay

Compensation is aligned according to three tiers within the United States:

• National: $128,000 - $160,000 (baseline tier for most of the U.S.)
• Premium: $137,900 - $172,400 (slightly elevated for higher cost-of-living areas like Los Angeles, CA and Seattle, WA)
• Premium Plus: $147,800 - $184,700 (for the most expensive areas like the San Francisco Bay area and New York City)

Salaries are determined by skills, prior experience, and work location. Eligible employees also receive annual bonuses based on individual performance and company success.

Benefits

• Multiple health insurance options.
• Flexible time off—take what you need.
• Retirement savings program with company contribution and after-tax contributions.
• Equity in a publicly-traded company and an Employee Stock Purchase Program.
• Family-forming benefits, fertility support, and up to 20 weeks of Parental Leave.
• Free therapy sessions, financial and professional coaching, and legal advice.
• Monthly stipend to support remote work.
• Annual “development dollars” to support growth and learning.
• Flexible First policy—work remotely or from the Oakland office.