Lead Product Manager, Risk Decisioning

present of AI; United States; Remote; USD 140,000 - 200,000; Full time

Job summary

Cleo in the United States is seeking a Risk Decisioning Lead to own the roadmap for the Pay Later product. You will decide who is approved and how much credit, balancing pricing, limits and loss risk as data constraints apply.

The ideal candidate has hands-on fintech credit or underwriting experience, fluency with SQL and A/B testing, and a track record of guiding models from concept to live deployment while working with legal, compliance and bank partners.

Qualifications

• Hands-on fintech credit or underwriting experience.
• Ability to balance pricing, limits and loss risk when data is thin.
• Comfort with SQL, A/B tests and US lending rules such as Reg Z and Reg B.

Responsibilities

• Own the risk decisioning roadmap for the Pay Later product.
• Decide who gets approved and how much credit.
• Collaborate with legal, compliance and bank partners to ensure regulatory alignment.

Skills

Fintech credit/underwriting experience

SQL

A/B testing

US lending rules (Reg Z/Reg B)

Model governance and lifecycle

Tools

SQL

Job description

This role owns the risk decisioning roadmap for the Pay Later product, which means deciding who gets approved and how much credit they receive. A strong candidate has hands-on fintech credit or underwriting experience, understands how models move from idea to live use, and can balance pricing, limits and loss risk when data is thin. Comfort with SQL, A/B tests and US lending rules such as Reg Z and Reg B matters, along with working well with legal, compliance and bank partners.

How it fits the AI era

Machine learning models already drive the core decisions here, so the work is less about building screens and more about guiding models, data and policy together. AI can speed up analysis, testing and fraud spotting, but people still set the risk appetite, weigh fairness and regulatory limits, and answer for the tradeoffs. Judgment on when a model is safe to roll out stays human.

How it builds AI experience

Someone in this role would gain close experience with the full life of credit models at a company that builds its product around an AI financial assistant: approval, testing, rollout and monitoring. Working with a credit bureau partner on what data feeds the models adds depth on data choices. To build this experience beforehand, practice reading model performance reports, designing experiments on credit decisions, and learning how lending rules shape what a model may use.

Worth showing

• Moving business metrics at scale
• SQL and A/B testing
• Reg Z and Reg B knowledge
• Working with ML and compliance

This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.

About Cleo

Conversational artificial intelligence financial assistant for personal budgeting, credit building, and savings management.