Head of Risk Product Strategy

Risk Product Strategy & Roadmap

Own the strategic roadmap for how risk capabilities are expressed in Imprint's product, spanning onboarding, underwriting, credit line management, authorization, fraud prevention, and account management.

Identify opportunities where risk intelligence can improve the customer experience: smarter instant approvals, dynamic credit limits, real time fraud detection that doesn't create unnecessary friction, proactive line increases for strong performers.

Define the sequencing and prioritization of risk product initiatives, balancing customer impact, revenue potential, loss reduction, and engineering feasibility.

Conduct ongoing audits of risk systems to identify gaps, inefficiencies, and high impact improvement opportunities.

Ensure every new product feature that touches a credit or risk decision has a clear risk strategy before it ships, not after.

Credit Decisioning Architecture

Own the strategic design of Imprint's credit decisioning framework: how applications are evaluated, how lines are assigned and managed, how step ups and step downs work, and how authorization rules balance fraud prevention with customer experience.

Partner with data science to define where and how models are deployed in the product, what signals they consume, and how their outputs translate into customer facing decisions.

Drive the evolution from static rule based decisioning toward dynamic, signal rich systems that adapt to customer behavior in real time.

New Product & Partner Launches

Define the risk product blueprint for new partner launches: how underwriting, line assignment, fraud controls, and servicing logic should be configured for each new program based on partner economics and target customer profile.

Ensure new launches are instrumented for rapid learning. The right data is captured, the right holdouts are in place, and the feedback loop from early performance to strategy adjustment is built in from day one.

Identify opportunities to extend risk capabilities across the portfolio, where a solution built for one partner can be generalized and deployed to others.

Measurement & Optimization

Define the KPI framework for risk product performance, connecting decisioning quality to downstream outcomes (approval rates, activation, utilization, loss rates, customer satisfaction).

Build the feedback loops that turn portfolio performance data into product improvements, ensuring the system learns and compounds over time.

Establish a test and learn discipline for risk product changes: structured experimentation, clean measurement, and rigorous readouts that separate signal from noise.

Self serve on data analysis using SQL and analytics tooling to identify trends and surface insights independently.

Leverage AI tools (e.g., Claude) to accelerate analysis, synthesis, and strategy development.

Qualifications

• 10+ years of experience spanning risk strategy and product strategy in consumer lending, cards, or fintech, with meaningful time on both sides of the risk product boundary.
• Deep understanding of credit card economics end to end: underwriting, line management, authorization, loss forecasting, and how product decisions flow through to portfolio P&L.
• Proven track record of building risk capabilities that are embedded in product, not layered on top. You've shipped features where risk logic was a core design element.
• Strong technical fluency: comfortable with SQL, familiar with how ML models are built and deployed, able to self serve on data and engage with engineering on system architecture without being an engineer.
• Experience defining and prioritizing product roadmaps, writing strategic documents, and driving cross functional alignment at the leadership level.
• Judgment and credibility to operate at the intersection of risk (conservative by nature) and product (biased toward speed). You know when to push for more velocity and when to pump the brakes.
• Exceptional communication skills: you can explain a complex risk product tradeoff to a brand partner, a CFO, or an engineer and have all three walk away with clarity.
• Comfortable working with AI tools (e.g., Claude) as a core part of the workflow.

Nice to Have

• Experience with machine learning concepts or Python-based modeling (depth not required, but familiarity valued).
• Background managing or coordinating across multiple risk-focused teams or functions.
• Exposure to consumer lending, credit card, or BNPL products.
• Experience operating at L5/L6 scope in a high-growth, fast-moving environment.