Remote Senior Product Manager - Fraud & Risk Strategy

Ladders; United States; Remote; USD 201,000 - 251,000; Full time

Benefits offered by this job

Equity options

RSUs

Comprehensive benefits

Salary reviews

Geo-based offers

Job summary

Ladders is seeking a Senior Product Manager - Fraud to lead the product strategy for fraud prevention and risk across the customer journey. This remote role balances security, compliance, and user experience while building scalable solutions that reduce fraud and improve operational efficiency.

Collaboration with data science, risk, and cross-functional teams is essential to drive automated decisioning and real-time systems.

Qualifications

• 7+ years of product management experience in fraud or risk.
• Strong empathy for customers and awareness of risk friction.
• Experience with automated decisioning systems and ML models.
• Analytical skills to translate data into actions.
• Proven cross-functional leadership balancing risk, compliance, and CX.
• Excellent communication to convey complex risk concepts.
• Ability to navigate ambiguity and make informed decisions.

Responsibilities

• Shape the strategy and roadmap for fraud prevention across areas.
• Design and execute strategies to mitigate fraud and risk experience.
• Craft user journeys balancing risk signals with UX.
• Build tools for risk and support teams to manage case volume.
• Collaborate with data science to improve ML models continuously.
• Establish metrics to measure risk effectiveness and CX impact.
• Support scaling of risk capabilities across products.

Skills

Fraud product mgmt

Risk management

Cross-functional leadership

Data analytics

Communication skills

Tools

ML models

Real-time data pipelines

Job description

Ladders is seeking a Senior Product Manager - Fraud to lead the product strategy for fraud prevention and risk across the customer journey. This remote role balances security, compliance, and user experience while building scalable solutions that reduce fraud and improve operational efficiency.

Collaboration with data science, risk, and cross-functional teams is essential to drive automated decisioning and real-time systems.