Senior Product Manager, Loyalty & Rewards (Fintech)

Affirm; Minneapolis (MN); Remote; USD 204,000 - 290,000; Full time

Benefits offered by this job

Health coverage for you and dependents

Monthly stipends for tech setup and WH

Flexible time off and generous holiday

Job summary

Affim is building a consumer loyalty program from the ground up. You will own the vision, roadmap, and rewards design across app, checkout, and post-purchase surfaces to drive adoption and retention.

You will partner with Risk, Credit, Legal, Compliance, Finance and Marketing to ensure compliant, transparent rewards while accelerating learning with data-driven experiments in a remote-first US environment.

Qualifications

• 8+ years in Product Management with consumer mobile apps or fintech.
• Experience building loyalty or rewards programs and measuring outcomes.
• Track record launching products from scratch and driving adoption.
• Owned repeat usage, cohort retention, or share of wallet metrics.

Responsibilities

• Own the vision and roadmap for Affim’s consumer loyalty program across quarters.
• Launch the first version of rewards and tiers with earn mechanics and redemption.
• Build engagement loops to drive weekly usage and long-term loyalty.
• Own program economics: reward liability, funding mix, and payback.
• Set up measurement foundations for LTV and incrementality testing.
• Collaborate with Risk, Credit, Legal, Compliance, Finance and Marketing to design compliant rewards.

Skills

Product management

Consumer mobile apps

Fintech / neobank

Cross-functional leadership

Experiment design

SQL

Analytics tools

Education

Bachelor's degree or equivalent

Tools

SQL

Amplitude

Python

Job description

Affim is building a consumer loyalty program from the ground up. You will own the vision, roadmap, and rewards design across app, checkout, and post-purchase surfaces to drive adoption and retention.

You will partner with Risk, Credit, Legal, Compliance, Finance and Marketing to ensure compliant, transparent rewards while accelerating learning with data-driven experiments in a remote-first US environment.