Staff Risk Analyst

Ladders; United States; Remote; USD 174,000 - 246,000; Full time

Benefits offered by this job

Remote work flexibility

Equity options

Comprehensive benefits

Job summary

Ladders is seeking a Staff Risk Analyst to shape credit risk policy and portfolio performance in a fast-moving fintech environment. You will collaborate with Product, Machine Learning, and cross-functional teams to turn analysis into practical policy improvements and build reporting frameworks for risk decision-making. Location: Remote - US-based candidates only.

Compensation: $173,928 – $245,773 annually. This role emphasizes risk policy optimization, experimentation, forecasting, and clear

Qualifications

• 7+ years of experience in credit risk analytics or related fintech fields.
• Expert in SQL and proficient in Python for data analysis.
• Strong fintech risk fundamentals, including limit/policy and portfolio monitoring.
• Experience with A/B testing and translating results into actionable insights.
• Forecasting and curve-based modeling techniques experience.
• Strong communication skills for conveying analytical findings.
• Ability to collaborate across teams including Machine Learning and Product.

Responsibilities

• Own policy optimization for member credit limits balancing retention and risk exposure.
• Design and evaluate policy experiments and A/B tests, translating results into policy changes.
• Manage forecasting and reporting infrastructure for risk and portfolio performance visibility.
• Explore data to identify opportunities for refining risk management strategies.
• Define performance metrics and create reports and dashboards for monitoring.
• Collaborate with Machine Learning and Product teams to implement analysis into policy changes.
• Monitor deployed models for performance and stability, flagging issues for retraining.

Skills

Experience

SQL

Python

Fintech risk knowledge

A/B testing

Forecasting

Communication

Cross-functional collaboration

Job description

For our client, we are seeking a Staff Risk Analyst to join the team of a leader in the Finance & Insurance space.

This role will shape credit risk policy and portfolio performance for a fast-moving fintech environment, with a strong focus on balancing growth, retention, and risk exposure. You will partner closely with Product, Machine Learning, and other cross-functional teams to turn analysis into practical policy improvements. The position also calls for building clear reporting and monitoring frameworks that strengthen decision-making across the risk function.

Location: Remote - US based candidates only, no visa sponsorship available

Compensation: $173,928 – $245,773 annually

Responsibilities

• Own policy optimization for member credit limits, balancing retention and risk exposure
• Design and evaluate policy experiments and A/B tests, translating results into policy changes
• Manage forecasting and reporting infrastructure for risk and portfolio performance visibility
• Explore data to identify opportunities for refining risk management strategies
• Define performance metrics and create reports and dashboards for monitoring
• Collaborate with Machine Learning and Product teams to implement analysis into policy changes
• Monitor deployed models for performance and stability, flagging issues for retraining

Qualifications

• 7+ years of experience in credit risk analytics or related fields, preferably in fintech
• Expert in SQL and proficient in Python for data analysis
• Knowledge of fintech risk fundamentals, including limit/max policy and portfolio monitoring
• Experience with A/B testing and translating results into actionable insights
• Familiarity with forecasting and curve-based modeling techniques
• Strong communication skills for conveying analytical findings
• Ability to collaborate across teams, including Machine Learning and Product

Benefits

• Remote work flexibility with in-office requirements for local employees
• Equity options in addition to salary
• Comprehensive benefits package

Our client is an equal opportunity employer. We encourage you to apply even if you don't meet every qualification- your background could be exactly what this team needs.